Search Results - predicting a difference (evolutionary OR evolution) algorithm

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    Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

    Published 2024
    “…Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. Post-optimization ANN model was trained using eleven different leaning algorithms. …”
    Article
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    Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

    Published 2012
    “…This paper proposes a penalty based differential evolution (P-DE) for extracting the parameters of solar photovoltaic (PV) modules at different environmental conditions. …”
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    Article
  3. 3

    A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus by Megat Yunus, Puteri Nor Ashikin

    Published 2023
    “…This thesis presents a new algorithm for output prediction and online monitoring in a Grid-Connected Photovoltaic (GCPV) system based on an artificial neural network. …”
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    Thesis
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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    Article
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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    Article
  7. 7

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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    Thesis
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    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

    Published 2017
    “…In this study, a hybrid evolutionary algorithm model (HPSOGA) and linear programming (LP) has been developed for optimizing the operation of reservoirs with the objectives of maximizing hydroelectric power generation, meeting the water demand for agricultural purposes and predicting the cost and estimating amount of agriculture products. …”
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    Thesis
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    Hyper-Heuristic Evolutionary Approach for Constructing Decision Tree Classifiers by Kumar, Sunil, Ratnoo, Saroj, Vashishtha, Jyoti

    Published 2021
    “…Finding optimal values for the hyper parameters of a decision tree construction algorithm is a challenging issue. …”
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    Article
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    Identification and predictive control of spray tower system using artificial neural network and differential evolution algorithm by Danzomo, Bashir A., Salami, Momoh Jimoh Eyiomika, Khan, Md. Raisuddin

    Published 2015
    “…This includes the use of an artificial neural network (ANN) based predictive control strategy and differential evolution (DE) optimization algorithm to determines the optimal control signal, uk (liquid droplet size, dD) by minimizing the cost function such that the output is set below the allowable PM concentration. …”
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    Proceeding Paper
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    Machine learning modeling for radiofrequency electromagnetic fields (RF-EMF) signals from mmWave 5G signals by Al-Jumaily, Abdulmajeed, Sali, Aduwati, Riyadh, Mohammed, Wali, Sangin Qahtan, Li, Lu, Osman, Anwar Faizd

    Published 2023
    “…Moreover, in a 1-minute duration, the difference between the predicted and measured values reached 0.2 less channels. …”
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    Article
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    Inclusive Multiple Model Using Hybrid Artificial Neural Networks for Predicting Evaporation by Ehteram M., Panahi F., Ahmed A.N., Mosavi A.H., El-Shafie A.

    Published 2023
    “…In this study, artificial neural network (ANN) is coupled with several evolutionary algorithms, i.e., capuchin search algorithm (CSA), firefly algorithm (FFA), sine cosine algorithm (SCA), and genetic algorithm (GA) for robust training to predict daily evaporation of seven synoptic stations with different climates. …”
    Article
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    Hybrid Metaheuristic Algorithm and Metaheuristic Performance Measurement for Solving University Course Timetabling Problem by Md Sultan, Abu Bakar

    Published 2007
    “…This research focused on the implementation of an hybrid evolutionary metaheuristic namely Two_point Hybrid Evolutionary Algorithm (Tp_HEA) on university course timetabling problem instances (UCTP). …”
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    Thesis
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    Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images by Farzan, Ali

    Published 2015
    “…So, a rank based feature selection algorithm is proposed to address these issues. …”
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    Thesis