Search Results - (( data integration method algorithm ) OR ( based optimization method algorithm ))
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1
Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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2
Data clustering using the bees algorithm
Published 2007“…This paper proposes a clustering method that integrates the simplicity of the k-means algorithm with the capability of the Bees Algorithm to avoid local optima. …”
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3
Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…This paper presents a novel discrete Whale Optimization Algorithm approach, integrating the strengths of population-based and local-search algorithms for addressing the examination timetabling problem, a significant challenge many educational institutions face. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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5
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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6
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…In this paper we propose an intrusion detection method that combines Fuzzy Clustering and Genetic Algorithms. …”
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7
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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8
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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9
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…Firstly, a new strategy based on a combined method (i.e. single-objective Gravitational Search (GSA) with Bat Algorithm (BAT) (SOGS-BAT)) algorithm is proposed in which relies on the closed interval between 0 and 1 to avoid falling into local search. …”
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10
A harmony search algorithm for university course timetabli
Published 2012“…The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. …”
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Optimization of RFID network planning using MDB-FA method
Published 2017“…The generated data are utilized as an input representation to apply into firefly algorithm based on Density-Based Algorithm (DBSCAN) to find the optimal network solution. …”
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…In order to improve the effectiveness of intrusion detection systems (IDSs), data analysis methods such as data mining and classification methods are often integrated with IDSs. …”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…However, their performances are not well optimized. This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. …”
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A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications
Published 2025“…Validation against conventional methods and state-of-the-art algorithms confirmed the superior performance of the proposed approach. …”
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15
An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs
Published 2018“…In order to improve the effectiveness of intrusion detection systems (IDSs), data analysis methods such as data mining and classification methods are often integrated with IDSs. …”
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Teletraffic performance of mobile cellular channel assignment using genetic algorithm
Published 2023“…Teletraffic performance of channel assignment strategy with and without genetic algorithm (GA) integration is presented in this paper. …”
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Benchmarking routing algorithms in NoC-based MPSoCs using guaranteed convergence arithmetic optimization with artificial neural networks and fuzzy MCDM
Published 2024“…Whereas phase 2 integrates the fuzzyweighted zero-inconsistency method and the fuzzy decision-by-opinion score method. …”
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Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan
Published 2025“…The method involves collecting data from the solar energy project of UiTM Kampus Dungun, implementing GA for optimization, and evaluating its performance based on the fitness value and convergence trends. …”
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Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif
Published 2024“…This thesis presents two innovative methods that holistically address these challenges at algorithmic and data levels to enhance heart disease detection. …”
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