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  1. 1
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  2. 2
    Electricity distribution network for low and medium voltages based on evolutionary approach optimization

    Electricity distribution network for low and medium voltages based on evolutionary approach optimization by Hasan, Ihsan Jabbar

    Published 2015
    “…The proposed algorithm has been evaluated on the two types of distribution network models which are the distribution network model with 500 customers that includes LV residential and commercial loads as well as MV distribution network, and 164 nodes in MV level. …”
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  3. 3
    Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine

    Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine by Alemu Lemma, Tamiru, Rangkuti, Chalillullah, Mohd Hashim, Fakhruldin

    Published 2009
    “…In this paper the result of an attempt to develop a substitute nonlinear model based on multilayer neural network (MLNN) and evolutionary algorithm (EA) for a single-shaft gas turbine having IGVs and VSVs is presented. …”
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  4. 4
    Optimal DG Placement and Sizing for Voltage Stability Improvement Using Backtracking Search Algorithm

    Optimal DG Placement and Sizing for Voltage Stability Improvement Using Backtracking Search Algorithm by Ruhaizad, Ishak, Azah, Mohamed, Abdalla, Ahmed N., Mohd Zamri, Che Wanik

    Published 2014
    “…A new evolutionary algorithm known as backtracking search algorithm (BSA) is opted in solving the optimization problem. …”
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  5. 5
    A hybrid optimization technique for solving economic emission load dispatch problems

    A hybrid optimization technique for solving economic emission load dispatch problems by Aisyah binti Nordin

    Published 2023
    text::Final Year Project
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  6. 6
    Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction

    Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

    Published 2021
    “…Also, it does not easily fall into local optima. The evolutionary algorithm can be used to optimize the number of its hidden layer nodes. …”
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  7. 7
    Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin

    Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

    Published 2014
    “…In order to ensure that the proposed technique is suitable for on-line application, a novel intelligent based technique is presented to predict the optimal output of DG and optimal undervoltage load shedding at various loading conditions. …”
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  8. 8
    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming

    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.…”
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  9. 9
    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks

    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

    Published 2015
    “…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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  10. 10
    Chaotic local search based algorithm for optimal DGPV allocation

    Chaotic local search based algorithm for optimal DGPV allocation by Mustaffa S.A.S., Musirin I., Othman M.M., Zamani M.K.M., Kalam A.

    Published 2023
    “…In this paper, Chaotic Mutation Immune Evolutionary Programming (CMIEP) algorithm is used as the optimization method while the chaotic mapping was employed in the local search for optimal location and sizing of DGPV. …”
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  11. 11
    Power system intentional islanding for different contingency scenarios using discrete optimization technique

    Power system intentional islanding for different contingency scenarios using discrete optimization technique by Nur Zawani Binti Saharuddin

    Published 2023
    “…The initial intentional islanding solution was determined using graph theory approach, to facilitate the proposed MDEP algorithm in determining the optimal intentional islanding strategy. …”
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  12. 12
    PID controller adjustment for MA-LFC by using imperialist competitive algorithm

    PID controller adjustment for MA-LFC by using imperialist competitive algorithm by Soheilirad, Mohammadsoroush, Farzan, Payam, Othman, Mohammad Lutfi, Karami, K., Hojabri, Mojgan

    Published 2013
    “…In this paper a new evolutionary computing method based on Imperialist Competitive Algorithm (ICA) is used for tuning the elements of a PID controller which is applied in a Multi Area Load Frequency Control System (MA-LFC). …”
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  13. 13
    Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali

    Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali by Mohd Ali, Nur Zahirah

    Published 2019
    “…CEPSO integrates the element of cloning and swarm in the original Evolutionary Programming algorithm. CEPSO is initially used to optimize the location and sizing of FACTS devices for compensation scheme. …”
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  14. 14
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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  15. 15
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. …”
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  16. 16
    Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets

    Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Mohammad, Omar Abdelaziz

    Published 2019
    “…The performance of the proposed algorithm is compared with DBN and is evaluated using performance metrics. …”
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  17. 17
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. …”
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  18. 18
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

    Published 2023
    “…This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. …”
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  19. 19
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. …”
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  20. 20
    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. …”
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