Application of Soft Computing Techniques for Water Quantity and Quality Modeling

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Misc{Yadav:thesis,
  author =       "Basant Yadav",
  title =        "Application of Soft Computing Techniques for Water
                 Quantity and Quality Modeling",
  school =       "Department of Civil Engineering, Indian Institute of
                 Technology Delhi",
  year =         "2017",
  address =      "Delhi, India",
  month =        "19 " # may,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.iitd.ac.in/content/basant-yadav-19052017",
  abstract_url = "http://www.iitd.ac.in/sites/default/files/phd/2013CEZ8051.pdf",
  abstract =     "Four water management problems are studied using
                 advanced simulation and optimization techniques. This
                 study is divided in two parts, the first part deals
                 with water quantity management problems whereas the
                 second part deals with water quality management
                 problems. In the first part, two water quantity
                 management problems are studied that include prediction
                 of discharge in rivers and groundwater level
                 predictions. In the second part of the study, two water
                 quality management problems are studied, that include
                 cost estimation of in-situ bioremediation and modelling
                 of saltwater intrusion in coastal aquifer.

                 Discharge forecasting in natural rivers is a
                 complicated procedure because of uncertainties involved
                 in the behaviour of the flood wave movement. This
                 further leads to solving complex problems of
                 hydrological modelling using soft computing techniques
                 (data-driven models). In real time flood forecasting
                 problems, the data generation is a continuous process.
                 In short term flood forecasting where the accuracy of
                 flood peak value and time to peak are critical,
                 frequent model updating becomes unavoidable. An
                 accurate discharge prediction in the least possible
                 time using online sequential extreme learning machine
                 (OS-ELM) can help policy makers and engineers design a
                 flood control policy and flood warning systems. OS-ELM
                 has not only been used in predictions for hydrological
                 systems, but also for other areas related to
                 environmental sciences. Similarly, a precise prediction
                 of groundwater level using ELM would be very helpful to
                 plan a groundwater abstraction policy in areas where
                 groundwater fluctuations is very high. In case of an
                 in-situ bioremediation system design, the remediation
                 cost can be considerably reduced when an efficient and
                 fast simulator like ELM is adopted. Further, the
                 inclusion of biological clogging of wells while
                 optimizing the cost in in-situ remediation provide a
                 realistic view of the remediation cost. Likewise, the
                 new soft computing techniques like SVM and ELM are a
                 good alternative to the traditional soft computing
                 techniques like ANN and found to be of immense
                 importance while designing the management strategy to
                 control seawater intrusion in coastal areas.",
}

Genetic Programming entries for Basant Yadav

Citations