Search Results - (( solution location optimization algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly
Published 2023“…Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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Solving vehicle routing problem by using improved genetic algorithm for optimal solution
Published 2023“…Bus transportation; Buses; Cost reduction; Costs; Education; Genetic algorithms; Location; Optimal systems; Routing algorithms; Students; Transportation; Transportation routes; Vehicle routing; Vehicles; Capacitated vehicle routing problem; Crossover operations; Economic interests; Evaluation criteria; Optimal solutions; Transportation cost; Vehicle routing problem; Vehicle Routing Problems; Problem solving…”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution
Published 2017“…To achieve an optimal solution for VRP with the accompanying targets: (1) To reduce the distance and the time for all paths this leads to speedy the transportation of customers to their locations, (2) To implement the capacitated vehicle routing problem (CVRP) model for optimizing the solutions. …”
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Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system
Published 2022“…They are also applied to optimize a type-2 fuzzy logic controller for an inverted pendulum system in comparison to SDA, Spotted Hyena Optimizer, Tunicate Swarm Algorithm, and Sooty Tern Optimization Algorithm. …”
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Development of improved metaheuristic algorithms for modelling and control of a flexible manipulator system
Published 2019“…The aim of the single type algorithms is to improve the algorithms capability to find an optimal solution. …”
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The optimization of technical trading strategy using genetic algorithm approach / Khairunnisa Musa
Published 2006“…Results from the function optimization shows that STDGA is effective and efficient in locating the optimal solution (the maximum value of the Sharpe Ratio). …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…An optimal power flow (OPF) solution is an essential approach in electric power system operation. …”
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Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…Stochastic-type algorithms have shown good performance in locating the global optima in optimization problems, even in difficult search spaces [1). …”
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Research Reports -
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A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method
Published 2018“…Furthermore, the process of detected an object in every frame is time consuming as the entire frame must be detected to precisely locate the object system. Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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An improved bat algorithm with artificial neural networks for classification problems
Published 2016“…Then, the proposed BAGD algorithm is frnther hybridized with Simulated Annealing (SA) and Genetic Algorithm (GA) to perform two stage optimization in which the former algorithm finds the optimal solution and the latter algorithm starts from where the first one is converged. …”
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Optimizing palm oil biomass collection: genetic algorithm approaches in solving location-routing problem
Published 2025“…The study aims to enhance the efficiency of palm oil biomass collection by identifying optimal locations for collection facilities and devising vehicle routing strategies at minimum costs. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm gives a pool of solutions rather than just one. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem
Published 2020“…The primary aim of this study is to propose a hybrid approach which combines Discrete Differential Evolution (DDE) algorithm and Tabu Search (TS) algorithm to enhance solutions of QAP model, to reduce the distances between the locations by finding the best distribution of N facilities to N locations, and to implement hybrid approach based on discrete differential evolution (HDDETS) on many instances of QAP from the benchmark. …”
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