Search Results - (( evolution optimisation system algorithm ) OR ( data implication optimisation algorithm ))
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Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm
Published 2017“…The proposed method is used to solve the optimisation problem in optimise the production of biochemical systems. …”
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Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage
Published 2023“…Electric power factor; Electric power transmission networks; Evolutionary algorithms; Optimization; Differential Evolution; Differential evolution algorithms; Distributed generation source; Multiple distributed generations; Optimal allocation; Optimisations; Power factorAbstract; Power system constraints; Distributed power generation; algorithm; distribution system; energy planning; operations technology; optimization…”
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids
Published 2023“…Our results have strong implications for SDM development, revealing the inconsistencies introduced by the choice of algorithm on scale optimisation, with GLM selecting broader scales than RF.…”
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Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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Smart site monitoring system / Muhammad Azmi and Muhammad Naim Mahyuddin
Published 2023“…These devices collect and transmit data to a centralised cloud-based platform. Advanced data analytics and machine learning algorithms process this data, enabling the system to detect potential safety hazards, monitor construction progress, and predict resource requirements. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
Published 2015“…To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO2 emissions. …”
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Modelling and simulation of drying process for ceramic membrane fabrication
Published 2015“…In fact, the drying process is one of the longest steps corresponding to various evolutions of parameters during the evaporation process. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Two sets of real-time data are presented in this work. The first one is related to the questionnaire data, consisting of 262 respondent samples, while the second set has 263 samples of pedestrian walking signals. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Two sets of real-time data are presented in this work. The first one is related to the questionnaire data, consisting of 262 respondent samples, while the second set has 263 samples of pedestrian walking signals. …”
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