Search Results - (( development account optimisation algorithm ) OR ( java binary classification algorithm ))
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems
Published 2010“…This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…Decision-makers have recently recognised the need for sustainable development. Multiobjective optimisation is the most reliable technique to solve multiple sustainable development goals. …”
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Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
Published 2011“…This research work is concluded with a software development. The package called Power Flow Analysis and DG Optimisation Tool (PFADOT) is developed using the Graphical User Interface (GUI) of MATLAB. …”
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Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm
Published 2025“…In order to demonstrate the effectiveness of the proposed algorithm, The outcomes of the simulation are juxtaposed with results obtained from the initial Pelican Optimisation Algorithm (POA), the Bat Algorithm, and the Improved Differential Evolutionary (IDE) Algorithm. …”
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Development of a particle swarm optimisation model for estimating the homogeneity of a mixture inside a newly designed CNG-H2-AIR mixer for a dual fuel engine: an experimental and...
Published 2018“…The particle swarm optimisation (PSO) algorithm was used to solve an optimisation problem and achieve this outcome. …”
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Case study: Optimisation of Federal Land Development Authority Jengka supply chain management using P-graph approach
Published 2015“…To address this issue, P-graph modelling is used as the methodology to solve combinatorial complexity of the biomass supply chain in Federal Land Development Authority Jengka. Few possible locations for building new biomass processing plant and storage hubs were introduced in the optimisation problem. …”
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
Published 2024“…Furthermore, cloud computing technology and association rule mining as the core technology based on analysis of domestic and foreign research. In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. …”
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Chaotic mutation immune evolutionary programming for photovoltaic planning in power system / Sharifah Azma Syed Mustaffa
Published 2020“…The element of chaotic local search is also integrated into the algorithm for better performance. A new optimisation engine was developed to address this issue. …”
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Gravitational energy harvesting system based on multistage braking technique for multilevel elevated car parking building
Published 2020“…The results showed that, 34.09% energy and 6.58% delay time have been improved using the proposed system and proposed optimised mass at 3.5 kg. Based on the MSBS experiment, the parameters used are being applied in developing an optimization model; both results are compared and obtained an 8.2% error. …”
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