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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…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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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…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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3
Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. The post-islanding frequency stability is maintained by optimizing the Load Frequency Control‘s parameters. …”
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4
Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025“…The results revealed that the used algorithms effectively mitigated water shortages and excess releases compared to the current operational strategy. …”
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Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach
Published 2021“…Backpropagation algorithm (BP), artificial bee colony (ABC), and genetic algorithm (GA) models were used to train the neural network (NN) parameters using the data collected from the CCD-based response equation. …”
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Design And Implementation Of Human Crowd Density Estimation System With Energy Harvesting In Wireless Sensor Network Platform
Published 2017“…These factors are then integrated into the proposed H-CDE algorithm. The H-CDE algorithm and its crowd classification yielded an average of 71.2 % accuracy in identifying the level of crowd density, which is the best compared to other algorithms found in the literature. …”
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