Search Results - (( selective implementation bees algorithm ) OR ( java application optimisation algorithm ))

An improved bees algorithm local search mechanism for numerical dataset by Al-Dawoodi, Aras Ghazi Mohammed

“…Furthermore, in this study the feature selection algorithm is implemented and tested using most popular dataset from Machine Learning Repository (UCI). …”
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Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

“…P-Median problem will be used as the main case study in implementing one of the Bee-Inspired algorithms to prove, illustrate example and show the characteristics of the selected concept…”
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An empirical study of double-bridge search move on subset feature selection search of bees algorithm by Al-dawoodi, Aras Ghazi Mohammed, Mahmuddin, Massudi

“…The application of Bees Algorithm in wrapper feature selection (BAFS) has been implemented but yet too far from perfect and has few weaknesses. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm by Ahirwal, M.K., Kumar, A., Singh, G.K.

“…In this paper, the Artificial Bee Colony (ABC) algorithm is applied to construct Adaptive Noise Canceller (ANC) for electroencephalogram (EEG)/Event Related Potential (ERP) filtering with modified range selection, described as Bounded Range ABC (BR-ABC). …”
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Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm by Mohamad Fadzil, Nur Hamisha Helanie

“…The implementation of ABC algorithm consists of four phases which are initialisation, employed, onlooker and scout bee phases. …”
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Selective harmonic elimination in multilevel inverter using hybrid APSO algorithm by Memon, Mudasir Ahmed, Mekhilef, Saad, Mubin, Marizan

“…In simulations, the performance of the proposed algorithm is compared with genetic algorithm, bee algorithm and particle swarm optimisation. …”
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Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation by Abdulwahhab, Mohanad Mazin

“…Firstly, we proposed a multi-criteria artificial bee colony hybrid with particle swarm optimisation algorithm (MC ABC-PSO) for evaluating the information gathered from the mobile nodes in the handover. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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An Intelligent Modeling of Oil Consumption by Chiroma, Haruna, Abdulkareem, Sameem, Muaz, Sanah Abdullahi, Abubakar, Adamu I., Sutoyo, Edi, Mungad , Mungad, Saadi, Younes, Sari, Eka Novita, Tutut, Herawan

“…The limitations associated with Levenberg-Marquardt (LM) Neural Network (NN) motivated this research to optimize the parameters of NN through Artificial Bee Colony Algorithm (ABC-LM) to build a model for the prediction of oil consumption. …”
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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

“…Comparative studies have been conducted with respect to Multi-Objective Modified Firefly Algorithm (MOMFA), Multi-Objective Artificial Bees Colony (MOABC) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

“…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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