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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…By using 'seen' and 'unseen' of electrical energy demand data were used to test the performance of the proposed algorithm. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Prediction of biochemical oxygen demand in Mexican surface waters using machine learning / Maximiliano Guzmán-Fernández ... [et al.]
Published 2021“…Pearson’s correlation and Forward Selection techniques were applied to identify the parameters with the most important contribution to prediction of biochemical oxygen demand. Two groups were formed and used as input to four machine learning algorithms. …”
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Conference or Workshop Item -
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Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025“…This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”
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Operating a reservoir system based on the shark machine learning algorithm
Published 2018“…In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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A Systematic Review Of Machine Learning Algorithms For Mental Health Detection Using Social Media Data
Published 2026journal::journal article -
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The efficacy of deep learning algorithm in classifying chilli plant growth stages
Published 2021“…Automatic plant growth monitoring has received considerable attention in recent years. The demand in this field has created various opportunities, especially for automatic classification using deep learning methods. …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023Conference Paper -
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…The proposed deep learning model renders faster without the use of SMOTE. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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Prediction of Pakistani Honey Authenticity through Machine Learning
Published 2022“…Therefore, this study proposes a novel classification model to address the aforementioned weaknesses by classifying the authenticity of Pakistani honey using machine learning algorithms and several physicochemical features. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar
Published 2024“…A significant way to minimize the errors is by using a machine learning approach that can predict reverse migration intelligently depending on the tested dataset. …”
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