Changes to Genetic Programing Bibliography since 2016/05/18

New and modified entries


  1. Abbaspour:2013:WSE Estimation of hydraulic jump on corrugated bed using artificial neural networks and genetic programming AkramAbbaspour.html DavoodFarsadizadeh.html MohammadAliGhorbani.html
  2. EvoBafin16Agapitosetal Genetic Programming with Memory For Financial Trading AlexandrosAgapitos.html AnthonyBrabazon.html MichaelO'Neill.html
  3. Aghbashlo:2016:Energy The use of ELM-WT (extreme learning machine with wavelet transform algorithm) to predict exergetic performance of a DI diesel engine running on diesel/biodiesel blends containing polymer waste MortazaAghbashlo.html ShahaboddinShamshirband.html MeisamTabatabaei.html PorLipYee.html YaserNabaviLarimi.html
  4. AguilarRivera:2015:ESA Genetic algorithms and Darwinian approaches in financial applications: A survey RubenAguilar-Rivera.html ManuelValenzuela-Rendon.html JJRodriguez-Ortiz.html
  5. Alemdag:2016:EG Modeling deformation modulus of a stratified sedimentary rock mass using neural network, fuzzy inference and genetic programming SelcukAlemdag.html ZGurocak.html AbdulkadirCevik.html AliFiratCabalar.html CandanGokceoglu.html
  6. AlShammari:2016:Energy Prediction of heat load in district heating systems by Support Vector Machine with Firefly searching algorithm EimanTamahAl-Shammari.html AframKeivani.html ShahaboddinShamshirband.html AliMostafaeipour.html PorLipYee.html DaliborPetkovic.html SudheerCh.html
  7. AsadiTashvigh:2015:Calphad A novel approach for estimation of solvent activity in polymer solutions using genetic programming AkbarAsadiTashvigh.html FarzinZokaeeAshtiani.html MohammadKarimi.html AhmadOkhovat.html
  8. Babaelahi:2016:Energy Analytical closed-form model for predicting the power and efficiency of Stirling engines based on a comprehensive numerical model and the genetic programming MojtabaBabaelahi.html HoseynSayyaadi.html
  9. Bahrami:2016:Fuel A novel approach for modeling and optimization of surfactant/polymer flooding based on Genetic Programming evolutionary algorithm PeymanBahrami.html PezhmanKazemi.html SedighehMahdavi.html HosseinGhobadi.html
  10. Barclay:2015:Procedia Generating Milling Tool Paths for Prismatic Parts Using Genetic Programming JackBarclay.html VimalDhokia.html AydinNassehi.html
  11. Bartoli:2016:ASC Predicting the effectiveness of pattern-based entity extractor inference AlbertoBartoli.html AndreaDeLorenzo.html EricMedvet.html FabianoTarlao.html
  12. BartschJr:2016:TJU Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the Bladder GeorgBartschJr.html AnirbanPMitra.html SheetalAMitra.html ArpitAAlmal.html KennethESteven.html DonaldGSkinner.html DavidWFry.html PeterFLenehan.html WilliamPWorzel.html RichardJCote.html
  13. Bashir:2016:ASC Opinion-Based Entity Ranking using learning to rank ShariqBashir.html WasifAfzal.html AbdulRaufBaig.html
  14. Berutich:2016:ESA Robust technical trading strategies using GP for algorithmic portfolio selection JoseManuelBerutich.html FranciscoLopez.html FranciscoLuna.html DavidQuintana.html
  15. Bhardwaj:2016:CMPB A novel genetic programming approach for epileptic seizure detection ArpitBhardwaj.html ArunaTiwari.html MRameshKrishna.html MVishaalVarma.html
  16. Bonakdari:2016:FMI Open channel junction velocity prediction by using a hybrid self-neuron adjustable artificial neural network HosseinBonakdari.html AmirHosseinZaji.html
  17. Bouaziz:2016:ASC Evolving flexible beta basis function neural tree using extended genetic programmin \& Hybrid Artificial Bee Colony SouhirBouaziz.html HabibDhahri.html AdelMAlimi.html AjithAbraham.html
  18. Bucur:2014:ASC The impact of topology on energy consumption for collection tree protocols: An experimental assessment through evolutionary computation DoinaBucur.html GiovanniIacca.html GiovanniSquillero.html AlbertoTonda.html
  19. Castelli:2015:ASC Prediction of relative position of CT slices using a computational intelligence system MauroCastelli.html LeonardoTrujillo.html LeonardoVanneschi.html AlesPopovic.html
  20. Castelli:2016:SEC Semantic genetic programming for fast and accurate data knowledge discovery MauroCastelli.html LeonardoVanneschi.html LucaManzoni.html AlesPopovic.html
  21. Castro:2015:OE Genetic programming and floating boom performance AlberteCastroPonte.html JLPerez.html JRRabunal.html GIglesias.html
  22. Chang:2015:ICNSC Improving the control of water treatment plant with remote sensing-based water quality forecasting model Ni-BinChang.html SanazImen.html
  23. Chang:2015:EI Diagnosis of the artificial intelligence-based predictions of flow regime in a constructed wetland for stormwater pollution control Ni-BinChang.html GolamMohiuddin.html AJamesCrawford.html KaixuBai.html Kang-RenJin.html
  24. Chen:2016:JPDC enDebug: A hardware-software framework for automated energy debugging JieChen.html GuruPrasadhVenkataramani.html
  25. Chivilikhin:2013:PV Solving Five Instances of the Artificial Ant Problem with Ant Colony Optimization DaniilChivilikhin.html VladimirUlyantsev.html AnatolyAbramovichShalyto.html
  26. Choi:2015:EE Physical habitat simulations of the Dal River in Korea using the GEP Model ByungwoongChoi.html Sung-UkChoi.html
  27. Clemente:2015:ASC Self-adjusting focus of attention in combination with a genetic fuzzy system for improving a laser environment control device system EddieHelbertClementeTorres.html FranciscoChavez.html FranciscoFernandezdeVega.html GustavoOlague.html
  28. Cojbasic:2016:PE Surface roughness prediction by extreme learning machine constructed with abrasive water jet ZarkoCojbasic.html DaliborPetkovic.html ShahaboddinShamshirband.html ChongWenTong.html SudheerCh.html PredragJankovic.html NedeljkoDucic.html JelenaBaralic.html
  29. Corn:2015:IFAC-PapersOnLine Designing model and control system using evolutionary algorithms MarkoCorn.html MajaAtanasijevic-Kunc.html
  30. daSilva:2015:CEE Use of graphics processing units for automatic synthesis of programs CleomarPereiradaSilva.html DouglasMotaDias.html CristianaBentes.html MarcoAurelioCavalcantiPacheco.html
  31. Demirhan:2015:ECM New horizontal global solar radiation estimation models for Turkey based on robust coplot supported genetic programming technique HaydarDemirhan.html YaseminKayhanAtilgan.html
  32. Dindarloo:2015:IJMST Prediction of blast-induced ground vibrations via genetic programming SaeidRDindarloo.html
  33. Diveev:2015:IFAC-PapersOnLine Variational Genetic Programming for Optimal Control System Synthesis of Mobile Robots AskhatDiveevIbraghimovich.html SIIbadulla.html NBKonyrbaev.html EYuShmalko.html
  34. Dolado:2016:ASOC Evaluation of Estimation Models using the Minimum Interval of Equivalence JoseJavierDoladoCosin.html DanielRodriguez.html MarkHarman.html WilliamBLangdon.html FedericaSarro.html
  35. Drach:2016:SSI Impedance spectroscopy analysis inspired by evolutionary programming as a diagnostic tool for SOEC and SOFC ZoharDrach.html ShaniHerskovici.html DomenicoFerrero.html PierluigiLeone.html AndreaLanzini.html MassimoSantarelli.html YoedTsur.html
  36. Elver:2016:ieeeHPCA McVerSi: A test generation framework for fast memory consistency verification in simulation MarcoElver.html VijayNagarajan.html
  37. Escalante:2016:ASC PGGP: Prototype Generation via Genetic Programming HugoJairEscalante.html MarioGraffGuerrero.html AliciaMorales-Reyes.html
  38. Fagiani:2015:Neurocomputing A review of datasets and load forecasting techniques for smart natural gas and water grids: Analysis and experiments MarcoFagiani.html StefanoSquartini.html LeonardoGabrielli.html SusannaSpinsante.html FrancescoPiazza.html
  39. Fathinasab:2016:Fuel On the determination of CO2-crude oil minimum miscibility pressure using genetic programming combined with constrained multivariable search methods MohammadFathinasab.html ShahabAyatollahi.html
  40. Fathinasab:2015:FPE A rigorous approach to predict nitrogen-crude oil minimum miscibility pressure of pure and nitrogen mixtures MohammadFathinasab.html ShahabAyatollahi.html AbdolhosseinHemmati-Sarapardeh.html
  41. Fattah:2016:JKSUES Improved oil formation volume factor (Bo) correlation for volatile oil reservoirs: An integrated non-linear regression and genetic programming approach KhaledAbdelFattahElshreef.html ALashin.html
  42. Fayolle:2016:CD An evolutionary approach to the extraction of object construction trees from 3D point clouds Pierre-AlainFayolle.html AlexanderPasko.html
  43. Garg:2015:JCP Energy conservation in manufacturing operations: modelling the milling process by a new complexity-based evolutionary approach AkhilGarg.html JasmineSiuLeeLam.html LiangGao.html
  44. Garg:2016:JCP Power consumption and tool life models for the production process AkhilGarg.html JasmineSiuLeeLam.html
  45. Garg:2015:JCPa Improving environmental sustainability by formulation of generalized power consumption models using an ensemble based multi-gene genetic programming approach AkhilGarg.html JasmineSiuLeeLam.html
  46. Garg:2016:JCPa Modeling multiple-response environmental and manufacturing characteristics of EDM process AkhilGarg.html JasmineSiuLeeLam.html LiangGao.html
  47. Garg:2016:CILS Framework based on number of basis functions complexity measure in investigation of the power characteristics of direct methanol fuel cell AkhilGarg.html BiranchiNarayanPanda.html DYZhao.html KangTai.html
  48. Garg:2015:Measurement Measurement of environmental aspect of 3-D printing process using soft computing methods AkhilGarg.html JasmineSiuLeeLam.html
  49. Garg:2015:Measurementa Model development based on evolutionary framework for condition monitoring of a lathe machine AkhilGarg.html VenkateshVijayaraghavan.html KangTai.html PravinMSingru.html VishalJain.html NikileshKrishnakumar.html
  50. Ghaddar:2016:EJOR Spare parts stocking analysis using genetic programming BissanGhaddar.html NizarSakr.html YawAsiedu.html
  51. Ghugare:2016:JEI Genetic programming based high performing correlations for prediction of higher heating value of coals of different ranks and from diverse geographies SuhasBGhugare.html SanjeevSTambe.html
  52. Goel:2015:JCA Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices PurvaGoel.html SanketBapat.html RenuVyas.html AmrutaTambe.html SanjeevSTambe.html
  53. GonzalezTaboada:2016:CBM Prediction of the mechanical properties of structural recycled concrete using multivariable regression and genetic programming IrisGonzalez-Taboada.html BelenGonzalez-Fonteboa.html FernandoMartinezAbella.html JuanLuisPerez.html
  54. Grochol:2016:ASC Evolutionary circuit design for fast FPGA-based classification of network application protocols DavidGrochol.html LukasSekanina.html MartinZadnik.html JanKorenek.html VKosar.html
  55. Harrison:2015:JCS A meta-analysis of centrality measures for comparing and generating complex network models KyleRobertHarrison.html MarioVentresca.html BeatriceOmbuki-Berman.html
  56. Hashim:2016:AR Selection of meteorological parameters affecting rainfall estimation using neuro-fuzzy computing methodology RoslanHashim.html ChandrabhushanRoy.html ShervinMotamedi.html ShahaboddinShamshirband.html DaliborPetkovic.html MilanGocic.html SiewChengLee.html
  57. Izadmehr:2016:JNGSE New correlations for predicting pure and impure natural gas viscosity MojtabaIzadmehr.html RezaShams.html MohammadHosseinGhazanfari.html
  58. Izadyar:2015:EB Intelligent forecasting of residential heating demand for the District Heating System based on the monthly overall natural gas consumption NimaIzadyar.html HwaiChyuanOng.html ShahaboddinShamshirband.html HosseinGhadamian.html ChongWenTong.html
  59. Izadyar:2015:Energy Appraisal of the support vector machine to forecast residential heating demand for the District Heating System based on the monthly overall natural gas consumption NimaIzadyar.html HosseinGhadamian.html HwaiChyuanOng.html Zeinabmoghadam.html ChongWenTong.html ShahaboddinShamshirband.html
  60. Jamiolahmadi:2015:IFAC-PapersOnLine A Genetic Programming Approach to Model Detailed Surface Integrity of Additive Manufacturing Parts SaeedJamiolahmadi.html AhmadBarari.html
  61. Jiang:2015:AEI Rough set and PSO-based ANFIS approaches to modeling customer satisfaction for affective product design HuiminJiang.html CheKitKwong.html KWMSiu.html YingLiu.html
  62. Johnson:2013:IMSE Chapter 14 - Evolutionary Algorithms Applied to Electronic-Structure Informatics: Accelerated Materials Design Using Data Discovery vs. Data Searching DuaneDJohnson.html
  63. Kadlic:2014:PV Design of Continuous-time Controllers using Cartesian Genetic Programming BranislavKadlic.html IvanSekaj.html DanielPernecky.html
  64. Kalfat:2016:CS Genetic programming in the simulation of Frp-to-concrete patch-anchored joints RKalfat.html AliNazari.html RAl-Mahaidi.html JayGSanjayan.html
  65. Kariminia:2016:RSER A systematic extreme learning machine approach to analyze visitors' thermal comfort at a public urban space ShahabKariminia.html ShahaboddinShamshirband.html ShervinMotamedi.html RoslanHashim.html ChandrabhushanRoy.html
  66. Kattan:2016:IS GP made faster with semantic surrogate modelling AhmedKattan.html AlexandrosAgapitos.html Yew-SoonOng.html AteqAAlghamedi.html MichaelO'Neill.html
  67. Khan:2016:GPEM Dynamic feedback neuro-evolutionary networks for forecasting the highly fluctuating electrical loads GulMuhammadKhan.html FaheemZafari.html
  68. Khodadi:2016:IPM Genetic programming-based feature learning for question answering ImanKhodadi.html MohammadSanieeAbadeh.html
  69. Kisi:2015:AMC A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm OzgurKisi.html JalalShiri.html SepidehKarimi.html ShahaboddinShamshirband.html ShervinMotamedi.html DaliborPetkovic.html RoslanHashim.html
  70. Kisi:2015:CEA Long-term monthly evapotranspiration modeling by several data-driven methods without climatic data OzgurKisi.html HadiSanikhani.html MohammadZounemat-Kermani.html FaeghehNiazi.html
  71. Koc:2015:CILS A genetic programming-based QSPR model for predicting solubility parameters of polymers DilekImrenKoc.html MehmetLeventKoc.html
  72. Koc:2016:OE Stability assessment of rubble-mound breakwaters using genetic programming MehmetLeventKoc.html CanElmarBalas.html DilekImrenKoc.html
  73. Korkontzelos:2015:AIM Boosting drug named entity recognition using an aggregate classifier IoannisKorkontzelos.html DimitriosPiliouras.html AndrewDowsey.html SophiaAnaniadou.html
  74. Koshiyama:2015:ASC GPFIS-CLASS: A Genetic Fuzzy System based on Genetic Programming for classification problems AdrianoSoaresKoshiyama.html MarleyMariaBernardesRebuzziVellasco.html RicardoTanscheit.html
  75. Kwak:2016:AAP Predicting crash risk and identifying crash precursors on Korean expressways using loop detector data Ho-ChanKwak.html SeungyoungKho.html
  76. LaCava:2016:RE Automatic identification of wind turbine models using evolutionary multiobjective optimization WilliamLaCava.html KouroshDanai.html LeeSpector.html PaulFleming.html AlanWright.html MatthewALackner.html
  77. Letia:2013:PV Automatic Control Synthesis of Hydro-Power Systems TiberiuSLetia.html OctavianPCuibus.html MihaiHulea.html RMiron.html
  78. Lim:2016:CS Evaluation of ultimate conditions of FRP-confined concrete columns using genetic programming JianCLim.html MuratKarakus.html TogayOzbakkaloglu.html
  79. Liu:2015:Energy Prediction, parametric analysis and bi-objective optimization of waste heat utilization in sinter cooling bed using evolutionary algorithm FionaYanLiu.html JianYang.html Jing-yuWang.html Xu-gangDing.html Zhi-longCheng.html Qiu-wangWang.html
  80. Londhe:2015:PE Application of Geno-wavelet Technique to Improve the Location Specific Wave Forecasts SNLondhe.html PradnyaRDixit.html ShwetaNarkhede.html
  81. EvoIasp16Loughranetal Speaker Verification on Unbalanced Data with Genetic Programming RoisinLoughran.html AlexandrosAgapitos.html AhmedKattan.html AnthonyBrabazon.html MichaelO'Neill.html
  82. Luo:2015:EAAI Adaptive space transformation: An invariant based method for predicting aerodynamic coefficients of hypersonic vehicles ChangtongLuo.html ZongminHu.html Shao-LiangZhang.html ZonglinJiang.html
  83. Mahdiani:2016:Petroleum The most accurate heuristic-based algorithms for estimating the oil formation volume factor MohammadRezaMahdiani.html GhazalKooti.html
  84. Marrone:2016:PCS Finding Resilient and Energy-saving Control Strategies in Smart Homes StefanoMarrone.html UgoGentile.html
  85. Meshgi:2015:JH Development of a modular streamflow model to quantify runoff contributions from different land uses in tropical urban environments using Genetic Programming AliMeshgi.html PetraSchmitter.html TingFongMayChui.html VladanBabovic.html
  86. Mladenovic:2016:AES Extreme learning approach with wavelet transform function for forecasting wind turbine wake effect to improve wind farm efficiency IgorMladenovic.html DusanMarkovic.html MilosMilovancevic.html MiroljubNikolic.html
  87. Moghaddam:2016:Measurement The use of SVM-FFA in estimating fatigue life of polyethylene terephthalate modified asphalt mixtures TaherBaghaeeMoghaddam.html MehrtashSoltani.html HamedShahrokhiShahraki.html ShahaboddinShamshirband.html NoorzailyBinMohamedNoor.html MohamedRehanKarim.html
  88. Mohammadi:2015:Energy Predicting the wind power density based upon extreme learning machine KasraMohammadi.html ShahaboddinShamshirband.html PorLipYee.html DaliborPetkovic.html MazdakZamani.html SudheerCh.html
  89. Montana:2016:ESA Model-driven regularization approach to straight line program genetic programming JoseLuisMontanaArnaiz.html CesarLuisAlonso.html CruzEnriqueBorges.html CristinaTirnauca.html
  90. MorenoSalinas:2015:IFAC-PapersOnLine Symbolic Regression for Marine Vehicles Identification. DMoreno-Salinas.html EBesada-Portas.html JALopez-Orozco.html DChaos.html JesusManueldelaCruz.html JAranda.html
  91. Mousavi:2015:Measurement Using measured daily meteorological parameters to predict daily solar radiation SeyyedMohammadMousavi.html ElhamSMostafavi.html AlirezaJaafari.html ArefehJaafari.html FaribaHosseinpour.html
  92. Nahvi:2016:CEA Using self-adaptive evolutionary algorithm to improve the performance of an extreme learning machine for estimating soil temperature BehnazNahvi.html JafarHabibi.html KasraMohammadi.html ShahaboddinShamshirband.html OthmanSalehAlRazgan.html
  93. Naji:2016:Energy Estimating building energy consumption using extreme learning machine method SarehNaji.html AframKeivani.html ShahaboddinShamshirband.html UJohnsonAlengaram.html MohdZaminJumaat.html ZulkefliMansor.html MalreyLee.html
  94. Nazari:2015:ES Modelling of upheaval buckling of offshore pipeline buried in clay soil using genetic programming AliNazari.html PathmanathanRajeev.html JayGSanjayan.html
  95. Nicholson:2014:SHPSPCSHPBBS The machine conception of the organism in development and evolution: A critical analysis DanielJNicholson.html
  96. Nikolic:2016:Mechatronics Extreme learning machine approach for sensorless wind speed estimation VlastimirNikolic.html ShervinMotamedi.html ShahaboddinShamshirband.html DaliborPetkovic.html SudheerCh.html MohammadArif.html
  97. Olatomiwa:2015:SE A support vector machine-firefly algorithm-based model for global solar radiation prediction LanreOlatomiwa.html SaadMekhilef.html ShahaboddinShamshirband.html KasraMohammadi.html DaliborPetkovic.html SudheerCh.html
  98. Olyaie:2016:GF A comparative analysis among computational intelligence techniques for dissolved oxygen prediction in Delaware River EhsanOlyaie.html HamidZareAbyaneh.html AliDanandehMehr.html
  99. Oz:2016:SSI Analysis of impedance spectroscopy of aqueous supercapacitors by evolutionary programming: Finding DFRT from complex capacitance AlonOz.html ShaniHerskovici.html NatalyBelman.html ErvinTal-Gutelmacher.html YoedTsur.html
  100. Pan:2016:FPT Incorporating uncertainty in data driven regression models of fluidized bed gasification: A Bayesian approach IndranilPan.html DayaShankarPandey.html
  101. Panda:2016:Measurement Empirical investigation of environmental characteristic of 3-D additive manufacturing process based on slice thickness and part orientation BiranchiNarayanPanda.html AkhilGarg.html KShankhwar.html
  102. Pandey:2016:SEC Maintaining regularity and generalization in data using the minimum description length principle and genetic algorithm: Case of grammatical inference HariMohanPandey.html AnkitChaudhary.html DeeptiMehrotra.html GrahamKendall.html
  103. Patnaik:2016:TBS Application of genetic programming clustering in defining LOS criteria of urban street in Indian context AshishKumarPatnaik.html PrasantaKumarBhuyan.html
  104. Peluso:2015:PP A Statistical Analysis of the Scaling Laws for the Confinement Time Distinguishing between Core and Edge EmmanuelePeluso.html MGelfusa.html AMurari.html ILupelli.html PGaudio.html
  105. Protic:2015:Energy Forecasting of consumers heat load in district heating systems using the support vector machine with a discrete wavelet transform algorithm MilanProtic.html ShahaboddinShamshirband.html DaliborPetkovic.html AlmasAbbasi.html MissLaihaMatKiah.html JawedAkhtarUnar.html LjiljanaZivkovic.html MiomirRaos.html
  106. Rahdari:2016:CEE A two-level multi-gene genetic programming model for speech quality prediction in Voice over Internet Protocol systems FarhadRahdari.html MehdiEftekhari.html RezaMousavi.html
  107. Rathore:2015:PCS Predicting Number of Faults in Software System using Genetic Programming SantoshSRathore.html SandeepKumar.html
  108. Ravansalar:2016:JH A wavelet-linear genetic programming model for sodium (Na+) concentration forecasting in rivers MasoudRavansalar.html TaherRajaee.html MohammadZounemat-Kermani.html
  109. Russo:2016:SEC A distributed neuro-genetic programming tool MarcoRusso.html
  110. Sajjadi:2016:EB Extreme learning machine for prediction of heat load in district heating systems ShahinSajjadi.html ShahaboddinShamshirband.html MeysamAlizamir.html PorLipYee.html ZulkefliMansor.html AzizahAbdulManaf.html TorkiAAltameem.html AliMostafaeipour.html
  111. Saraiva:2016:IPM A multimodal query expansion based on genetic programming for visually-oriented e-commerce applications PatriciaCorreiaSaraiva.html JoaoMarcosBCavalcanti.html EdlenoSilvadeMoura.html MarcosAndreGoncalves.html RicardodaSilvaTorres.html
  112. Sedano:2015:PCS Towards Generating Essence Kernels Using Genetic Algorithms ToddSedano.html CecilePeraire.html JasonLohn.html
  113. Shamaei:2016:ASC Suspended sediment concentration estimation by stacking the genetic programming and neuro-fuzzy predictions EhsanShamaei.html MarjanKaedi.html
  114. Shamshirband:2016:RSER Assessing the proficiency of adaptive neuro-fuzzy system to estimate wind power density: Case study of Aligoodarz, Iran ShahaboddinShamshirband.html AframKeivani.html KasraMohammadi.html MalreyLee.html SitiHafizahAbdHamid.html DaliborPetkovic.html
  115. Shamshirband:2015:RSER A comparative evaluation for identifying the suitability of extreme learning machine to predict horizontal global solar radiation ShahaboddinShamshirband.html KasraMohammadi.html PorLipYee.html DaliborPetkovic.html AliMostafaeipour.html
  116. SheikhKhozani:2016:Measurement Application of a genetic algorithm in predicting the percentage of shear force carried by walls in smooth rectangular channels ZohrehSheikhKhozani.html HosseinBonakdari.html AmirHosseinZaji.html
  117. Silva-Belisario:thesis Contribution de l'apprentissage par simulation a l'auto-adaptation des systemes de production LorenaSilva-Belisario.html
  118. Soltani:2016:Neurocomputing Designing efficient discriminant functions for multi-category classification using evolutionary methods AbolfazlSoltani.html SeyedMohammadAhadi.html NedaFaraji.html SaeedSharifian.html
  119. Sotto:2016:Neurocomputing Studying bloat control and maintenance of effective code in linear genetic programming for symbolic regression LeoFrancosoDalPiccolSotto.html ViniciusVelosodeMelo.html
  120. DBLP:journals/computing/Squillero11 Artificial evolution in computer aided design: from the optimization of parameters to the creation of assembly programs GiovanniSquillero.html
  121. Tabatabaei:2016:EAAI Self-adjusting multidisciplinary design of hydraulic engine mount using bond graphs and inductive genetic programming SKarimTabatabaei.html SaeedBehbahani.html ClarenceWdeSilva.html
  122. TaghizadehMehrjardi:2016:Geoderma Digital mapping of soil organic carbon at multiple depths using different data mining techniques in Baneh region, Iran RTaghizadeh-Mehrjardi.html KNabiollahi.html RKerry.html
  123. Tahta:2015:ASC GenTrust: A genetic trust management model for peer-to-peer systems UgurErayTahta.html SevilSen.html AhmetBurakCan.html
  124. Tajeri:2015:IJRMMS Indirect estimation of the ultimate bearing capacity of shallow foundations resting on rock masses ShervinTajeri.html EhsanSadrossadat.html JafarBolouriBazaz.html
  125. Tripathi:2016:CMS Evolution of glass forming ability indicator by genetic programming ManwendraKTripathi.html SubhasGanguly.html ParthaDey.html PPChattopadhyay.html
  126. Vardhan:2016:Measurement Measurement of Stress Dependent Permeability of Unsaturated Clay KurugoduHarshaVardhan.html AnkitGarg.html JinhuiLi.html AkhilGarg.html
  127. Vijayaraghavan:2015:Measurement Development of energy consumption model of abrasive machining process by a combined evolutionary computing approach RVijayaraghavan.html AkhilGarg.html VenkateshVijayaraghavan.html LiangGao.html
  128. Vijayaraghavan:2016:JCP A finite element based data analytics approach for modeling turning process of Inconel 718 alloys VenkateshVijayaraghavan.html AkhilGarg.html LiangGao.html RVijayaraghavan.html GuoxingLu.html
  129. Villarreal:2016:Neurocomputing Synthesis of odor tracking algorithms with genetic programming BlancaLorenaVillarreal.html GustavoOlague.html JoseLuisGordillo.html
  130. Xia:2016:CN Closed-loop design evolution of engineering system using condition monitoring through internet of things and cloud computing MinXia.html TengLi.html YunfeiZhang.html ClarenceWdeSilva.html
  131. Yang:2015:EP Modeling the nexus between carbon dioxide emissions and economic growth GuangfeiYang.html TaoSun.html JianliangWang.html XiannengLi.html
  132. Yang:2016:ASC A chaotic time series prediction model for speech signal encoding based on genetic programming LeiYang.html JunxiZhang.html XiaojunWu.html YumeiZhang.html JingjingLi.html
  133. Guangfei_Yang:thesis Study on association rule retrieval and association rule-based classification using evolutionary computation GuangfeiYang.html
  134. Yang:2016:Neurocomputing Surface EMG based handgrip force predictions using gene expression programming ZhongliangYang.html YumiaoChen.html ZhichuanTang.html JianpingWang.html
  135. Zamir:2016:CMPB Detection of epileptic seizure in EEG signals using linear least squares preprocessing ZRoshanZamir.html
  136. Zhao:2016:IS Multiobjective Optimization of Classifiers by Means of 3D Convex-Hull-Based Evolutionary Algorithms JiaqiZhao.html VitorBasto-Fernandes.html LichengJiao.html IrynaYevseyeva.html AsepMaulana.html RuiLi.html ThomasBack.html KeTang.html MichaelEmmerich.html
  137. Zuperl:2016:PE Surface roughness fuzzy inference system within the control simulation of end milling UrosZuperl.html FranciCus.html


  1. 1 Al-Sahaf:2015:EC Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances HarithAl-Sahaf.html MengjieZhang.html MarkJohnston.html
  2. 1 Azamathulla2012203 Flow discharge prediction in compound channels using linear genetic programming HaziMohammadAzamathulla.html AbdulrezaZahiri.html
  3. 14 Bokhari:2016:GI Optimising Energy Consumption Heuristically on Android Mobile Phones MahmoudABokhari.html MarkusWagner.html
  4. 1 Choi:2010:ICIP Computer-aided detection of pulmonary nodules using genetic programming Wook-JinChoi.html TaeSunChoi.html
  5. 1 BCK-thesis Genetic Programming Bias with Software Performance Analysis BrendanCody-Kenny.html
  6. 1 Cody-Kenny:2015:gi locoGP: Improving Performance by Genetic Programming Java Source Code BrendanCody-Kenny.html EdgarGalvanLopez.html StephenBarrett.html
  7. 4 deMelo:2015:GPTP Kaizen Programming for Feature Generation ViniciusVelosodeMelo.html WolfgangBanzhaf.html
  8. 1 eiben:2003:book Introduction to Evolutionary Computing GuszEiben.html JamesSmith.html
  9. 5 Elyasaf:2015:GPTP Casting the Problem of Mining RNA Sequence-Structure Motifs as One of Search and Learning Hyper-Heuristics for it AchiyaElyasaf.html PavelVaks.html NimrodMilo.html MosheSipper.html MichalZiv-Ukelson.html
  10. 17 Garciarena:2016:GI Evolutionary optimization of compiler flag selection by learning and exploiting flags interactions UnaiGarciarenaHualde.html RobertoSantana.html
  11. 1 Garg:2015:SEC A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance AkhilGarg.html VenkateshVijayaraghavan.html JasmineSiuLeeLam.html PravinMSingru.html LiangGao.html
  12. 3 Gustafson:2015:GPTP Using Genetic Programming for Data Science: Lessons Learned StevenMGustafson.html RamNarasimhan.html RaviPalla.html AishaYousuf.html
  13. 30 Helmuth:2015:GPTP Lexicase Selection For Program Synthesis: A Diversity Analysis ThomasHelmuth.html NicholasFreitagMcPhee.html LeeSpector.html
  14. 4 Hodjat:2015:GPTP Symbolic nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star BabakHodjat.html JormozShahrzad.html
  15. 1 Jamshidi:2001:AMC Autonomous control of complex systems: robotic applications MohammadJamshidi.html
  16. 19 Javadi:2010:ICCCBE Finite element analysis of three dimensional shallow foundation using artificial intelligence based constitutive model AkbarAJavadi.html AsaadFaramarzi.html AlirezaAhangar-Asr.html MouraMehravar.html
  17. 18 Kocsis:2016:GI Automatic Improvement of Apache Spark Queries using Semantics-preserving Program Reduction ZoltanKocsis.html JohnHDrake.html JerrySwan.html
  18. 4 Kommenda:2015:GPTP Evolving Simple Symbolic Regression Models by Multi-objective Genetic Programming MichaelKommenda.html GabrielKronberger.html MichaelAffenzeller.html StephanMWinkler.html BogdanBurlacu.html
  19. 4 Korns:2015:GPTP Highly Accurate Symbolic Regression with Noisy Training Data MichaelKorns.html
  20. 4 chrisgptp2015behavioral Behavioral Program Synthesis: Insights and Prospects KrzysztofKrawiec.html JerrySwan.html Una-MayO'Reilly.html
  21. 1 lacy2015forming Forming classifier ensembles with multimodal evolutionary algorithms StuartELacy.html MichaelALones.html StephenLSmith.html
  22. 7 langdon:2016:GI Benchmarking Genetically Improved BarraCUDA on Epigenetic Methylation NGS datasets and nVidia GPUs WilliamBLangdon.html AlbertVilella.html BrianYeeHongLam.html JustynaPetke.html MarkHarman.html
  23. 1 Lohpetch:thesis Evolutionary algorithms for financial trading DomeLohpetch.html
  24. 27 Lopez:2016:GI Genetic Programming: From design to improved implementation VictorRaulLopezLopez.html LeonardoTrujillo.html PierrickLegrand.html GustavoOlague.html
  25. 2 Lopez-Herrejon:2015:gi Genetic Improvement for Software Product Lines: An Overview and a Roadmap RobertoELopez-Herrejon.html LukasLinsbauer.html WesleyKGAssuncao.html StefanFischer.html SilviaReginaVergilio.html AlexanderEgyed.html
  26. 6 Ludwig:2016:GPEM Anthony Brabazon, Michael O'Neill, Sean McGarraghy: Natural computing algorithms Springer, 2015, 554 pp, ISBN: 978-3-662-43631-8 SimoneALudwig.html
  27. 4 McPhee:2015:GPTP Using Graph Databases to Explore Genetic Programming Run Dynamics NicholasFreitagMcPhee.html DavidDonatucci.html ThomasHelmuth.html
  28. 1 Neumann:2011:GPTP Computational Complexity Analysis of Genetic Programming - Initial Results and Future Directions FrankNeumann.html Una-MayO'Reilly.html MarkusWagner.html
  29. 1 oai:CiteSeerPSU:574087 Incremental Acquisition of Complex Visual Behaviour using Genetic Programming SimonPerkins.html
  30. 13 Petke:2016:GI Genetic Improvement for Code Obfuscation JustynaPetke.html
  31. 12 Popyack:2016:GPEM Gusz Eiben and Jim Smith: Introduction to evolutionary computing (second edition) Springer, 2015, 299 pp, ISBN: 978-3-662-44874-8 JeffreyLPopyack.html
  32. 8 ryan:1995:paragen Automatic conversion of programs from serial to parallel using Genetic Programming - The Paragen System PaulJWalsh.html ConorRyan.html
  33. 4 Silva:2015:GPTP Multiclass Classification Through Multidimensinoal Clustering SaraSilva.html LuisMunozDelgado.html LeonardoTrujillo.html VijayIngalalli.html MauroCastelli.html LeonardoVanneschi.html
  34. 1 Silva-Belisario:2015:ESA Using genetic programming and simulation to learn how to dynamically adapt the number of cards in reactive pull systems LorenaSilva-Belisario.html HenriPierreval.html
  35. 5 Sosa-Ascencio:2015:GPEM Grammar-based generation of variable-selection heuristics for constraint satisfaction problems AlejandroSosa-Ascencio.html GabrielaOchoa.html HugoTerashima-Marin.html SantiagoEnriqueConant-Pablos.html
  36. 4 Stijven:2015:GPTP Prime-Time: Symbolic Regression Takes its Place in Industrial Analysis SeanStijven.html Ekaterina_Katya_Vladislavleva.html ArthurKKordon.html MarkKotanchek.html
  37. 4 Tozier:2015:GPTP GP As If You Meant It: Real and Imaginary User Experience BillTozier.html
  38. 4 Truscott:2015:GPTP Predicting Product Choice with Symbolic Regression and Classification PhilipDTruscott.html
  39. 6 Vasicek:2016:GPEM Evolutionary design of complex approximate combinational circuits ZdenekVasicek.html LukasSekanina.html
  40. 2 Wagner:2014:CEC Single- and Multi-Objective Genetic Programming: New Runtime Results for SORTING MarkusWagner.html FrankNeumann.html
  41. 19 Wagner:2016:GI Speeding up the proof strategy in formal software verification MarkusWagner.html
  42. 1 oai:CiteSeerPSU:530668 Evolution of a Robotic Soccer Player MatthewWalker.html
  43. 8 White:2016:GI Guiding Unconstrained Genetic Improvement DavidRobertWhite.html
  44. 13 Woodward:2016:GI GP vs GI: if you can't beat them, join them JohnRWoodward.html ColinGJohnson.html AlexanderEIBrownlee.html
  45. 18 Woodward:2016:GIa Evals is not enough: why we should report wall-clock time JohnRWoodward.html AlexanderEIBrownlee.html ColinGJohnson.html
  46. 4 Worzel:2015:GPTP The Evolution of Everything (EvE) and Genetic Programming WilliamPWorzel.html

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