Search Results - (( developing building evolutionary algorithm ) OR ( java implementation tree algorithm ))
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Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings
Published 2025“…This paper introduces a novel Multi-Objective Evolutionary Mating Algorithm (MOEMA) designed to address the inherent challenges of optimizing comfort index and energy consumption in smart building systems. …”
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Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications
Published 2026“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction
Published 2025“…This paper presents a novel Evolutionary Mating Algorithm (EMA) hybridized with Artificial Neural Networks (ANN) for optimizing feature selection. …”
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Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris
Published 2019“…The proposed co-simulation process is developed by coupling building energy simulation (BES) software, Energy Plus with multi-objective evolutionary programming (MOEP) algorithm which is implemented in Matlab using coupling software, BCVTB. …”
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Chaotic mutation immune evolutionary programming for voltage security with the presence of DGPV
Published 2023“…Chaotic Mutation Immune Evolutionary Programming (CMIEP) is developed by integrating the piecewise linear chaotic map (PWLCM) in the mutation process in order to increase the convergence rate of the algorithm. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Building Fuzzy Inference Systems with Similarity Reasoning: NSGA II-based Fuzzy Rule Selection and Evidential Functions
Published 2014“…In both frameworks, SR is used to deduce unknown fuzzy rules based on similarity of the given and unknown fuzzy rules for building a Fuzzy Inference System (FIS). In this paper, we further extend our previous findings by developing (1) a multi-objective evolutionary model for fuzzy rule selection; and (2) an evidential function to facilitate the use of both frameworks. …”
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers
Published 2021“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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Student Luggage Storage System (SLSS) / Sofea Aida Sallehan
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Optimal load management strategy for enhanced time of use (ETOU) electricity tariff in Peninsular Malaysia / Mohamad Fani Sulaima
Published 2020“…Particle swarm optimization (PSO), evolutionary particle swarm optimization (EPSO), and ant colony optimization (ACO) algorithms were applied to optimize the simultaneous LM strategies of peak clipping, valley filling and load shifting in order to minimize the energy consumption and maximum demand costs, and improve economic indexes such as load factor and building economic efficiency response. …”
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