Search Results - ((((prediction algorithm) OR (selection algorithm))) OR (optimization algorithm))

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  1. 1

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…The second is the optimization of the best selected machine learning algorithms to further improve the efficiency and efficacy of the prediction. …”
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    Thesis
  2. 2

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

    Published 2017
    “…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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    Article
  3. 3

    Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii by Shafii, Muhammed Khaleeq

    Published 2012
    “…This project focuses on three main objectives to investigate the UPSR Examination of data for prediction result, to study the Clonal Selection algorithm of the term and to develop the Prediction of UPSR Result System using Clonal Selection Algorithm. …”
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    Thesis
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    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. …”
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    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

    Published 2026
    “…This research paper explores the performance of binary nature-inspired optimization algorithms as feature selection to enhance the identification of human activities using wearable technology. …”
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    Article
  8. 8

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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    Conference or Workshop Item
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    Evaluation of data mining models for predicting concrete strength by Wong, Chuan Ming

    Published 2024
    “…The best performing model is selected and used to generate different sets objective-function that will be selected and used in a Particle Swarm Optimization algorithm to solve a single objective optimization problem that finds the optimal values of each concrete feature to maximize the strength of concrete. …”
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    Final Year Project / Dissertation / Thesis
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    Imposed weighting factor optimization method for torque ripple reduction of IM fed by indirect matrix converter with predictive control algorithm by Uddin, M., Mekhilef, Saad, Rivera, M., Rodriguez, J.

    Published 2015
    “…The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. …”
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  12. 12

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…The second proposed algorithm uses SA to optimize the terms selection while constructing a rule. …”
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    Thesis
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    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
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    Thesis
  14. 14

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…In this research, the empirical experiments have been conducted for the five selected algorithms in the engineering optimization discipline, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS). …”
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    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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    Article
  17. 17

    Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction by Nor Farizan, Zakaria, Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2025
    “…This paper presents a novel Evolutionary Mating Algorithm (EMA) hybridized with Artificial Neural Networks (ANN) for optimizing feature selection. …”
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  18. 18

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…In its operation, the metaheuristic algorithm optimizes the feature selection process,which will later be processed using the classification algorithm.Three (3) meta-heuristics were implemented, namely Genetic Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm; the experiment was conducted, and the results were collected and analyzed. …”
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