Search Results - (evolutionary OR evolution) selection techniques

Refine Results
  1. 1
  2. 2

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…The median convergence traces have been compared with two different algorithms based on differential evolution, i:e: Ensemble of Constraint Handling Techniques (ECHT) and Stochastic Ranking Differential Evolution (SRDE). …”
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    Game-theoretic differential evolution for multiobjective optimization of green sand mould system by Ganesan, T., Vasant, P., Elamvazuthi, I., Shaari, K.Z.K.

    Published 2016
    “…In addition the standard metaheuristic, differential evolution is improved using concepts from evolutionary game theory. …”
    Get full text
    Get full text
    Article
  5. 5
  6. 6

    Harmonic Elimination Pulse Width Modulation Using Differential Evolution Technique For Three Phase Voltage Source Inverter by Kamisman, Norazelina

    Published 2018
    “…Differential Evolution (DE) has been gaining popularity among researchers as an effective yet simple evolutionary algorithm to solve the optimization problems. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    Operating Generator Selection Applied for Reactive Power Dispatched Using Evolutionary Programming Technique by Nor Rul Hasma, Abdullah, Ismail, Musirin, Muhammad Murtadha, Othman

    Published 2013
    “…This paper presents a new approach for selecting the operating generator performed optimally using Evolutionary Programming (EP) technique in power system. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Solving unit commitment problem with solar plant by using improved evolutionary programming / Mohamad Izazuddin Hassan by Hassan, Mohamad Izazuddin

    Published 2013
    “…The aim of this study is to solve the Unit Commitment Problem with Solar Plant using the Improved Evolutionary Programming technique. The objective of this study is to search for minimum operational cost while satisfying the ranging load demand, to compare the performance of Improve Evolutionary Programming with Evolutionary Programming before installing Solar Plant and after the installation. …”
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10

    Solving unit commitment problem with solar photovoltaic and wind energy generation by using multi-agent evolutionary programming technique / Putri Azimah Salleh by Salleh, Putri Azimah

    Published 2014
    “…Several Artificial Intelligence (AI) techniques such as Multi Agent and Evolutionary Programming were combine to produce Multi Agent Evolutionary Programming (MAEP) technique. …”
    Get full text
    Get full text
    Thesis
  11. 11

    Hybrid evolutionary barnacles mating optimization: a novel technique for economic load dispatch optimization / Nor Laili Ismail ... [et al.] by Ismail, Nor Laili, Musirin, Ismail, Dahlan, Nofri Yenita, Mansor, Mohd Helmi

    Published 2022
    “…Several case studies have been selected to evaluate the efficiency of HEBMO and compare it with the existing single optimization technique, Evolutionary Programming (EP), and Barnacles Mating Optimizer (BMO). …”
    Get full text
    Get full text
    Conference or Workshop Item
  12. 12

    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  13. 13
  14. 14

    Similarity reasoning-driven evolutionary fuzzy system for monotonic-preserving models by Jee, Tze Ling

    Published 2013
    “…The focus of this thesis is on fuzzy rule base reduction techniques, fuzzy rule selection techniques, Approximate Analogical Reasoning Schema (AARS), evolutionary computation techniques and monotonicity property of an FIS, in order to overcome these two shortcomings. …”
    Get full text
    Get full text
    Get full text
    Thesis
  15. 15

    A new islanding detection technique based on passive parameter using artificial neural network evolutionary programing / Aimie Nadia Ab Salam by Ab Salam, Aimie Nadia

    Published 2019
    “…The objective of this thesis is to design a new islanding detection technique for synchronous type of DG based on the most sensitive passive parameters by using Artificial Neural Network (ANN) Evolutionary Programming (EP). …”
    Get full text
    Get full text
    Thesis
  16. 16

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…The second improvement involves the incorporation of evolutionary operators from Differential Evolution algorithm at the end of each WOA iteration including mutation, crossover, and selection operators. …”
    Get full text
    Get full text
    Article
  17. 17

    Discrete Evolutionary Programming for Network Splitting Strategy: Different Mutation Technique by Saharuddin, Nur Zawani, Abidin, Izham Zainal, Mokhlis, Hazlie

    Published 2018
    “…The results show that three-level mutation technique produces better optimal splitting solution as compared to single mutation technique.…”
    Get full text
    Get full text
    Article
  18. 18

    Sediment transport prediction due to in-stream mining by evolutionary polynomial regression method / Nadiatul Adilah Ahmad Abdul Ghani by Ahmad Abdul Ghani, Nadiatul Adilah

    Published 2019
    “…This study investigates the use of Evolutionary Polynomial Regression (EPR) technique in genetic programming to predict sediment transport due to in-stream mining. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Medium term load forecasting using evolutionary programming-least square support vector machine by Yasin Z.M., Zakaria Z., Razak M.A.A., Aziz N.F.A.

    Published 2023
    “…In EP-LSSVM, the Radial Basis Function (RBF) Kernel parameters are optimally selected using Evolutionary Programming (EP) optimization technique for accurate prediction. …”
    Article
  20. 20