Search Results - (( java application optimisation algorithm ) OR ( using low (problems OR problem) algorithm ))
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1
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Secondly, an expert system using Java programming technology with two tiers of search engine was developed to perform a fast selection of candidate materials in huge volume. …”
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Thesis -
2
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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3
Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. …”
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4
Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems
Published 2024“…Furthermore, the original DA is only suitable for solving continuous optimization problems. Although there is a binary version of the algorithm, it cannot be directly used for solving discrete optimization problems like the Traveling Salesman Problem (TSP). …”
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5
Travelling Salesman Problem using Prim Algorithm in High Performance Computing
Published 2007“…TSP has been used in The Two-Period Travelling Salesman Problem Applied to Milk Collection in Ireland and Usefulness of Solution Algorithms of the Travelling Salesman Problem in the typing of Biological Sequences in a Clinical Laboratory Setting.…”
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Final Year Project -
6
Controlling algorithm for energy consumption of radio bandwidth to manage coverage area problem
Published 2024Conference Paper -
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Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
Published 2015“…Hybrid metaheuristic algorithms have the ability to produce better solution than stand-alone approach and no algorithm could be concluded as the best algorithm for scheduling algorithm or in general, for combinatorial problems.This study presents the low and high level hybridization of ant colony system and genetic algorithm in solving the job scheduling in grid computing.Two hybrid algorithms namely ACS(GA) as a low level and ACS+GA as a high level are proposed.The proposed algorithms were evaluated using static benchmarks problems known as expected time to compute model. …”
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Conference or Workshop Item -
8
Multi-objective service restoration in distribution networks using genetic algorithm
Published 2013“…This thesis presents a new approach of supply restoration service using the Genetic Algorithm. The GA is robust in searching a global optimal solution for the large-scale combinatorial optimization problems. …”
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9
Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…The codes of the scripting language are shown to easily use, concisely describe the algorithm in a directly publishable form and flexible for new problem creations. …”
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10
Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. …”
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11
INNOVATIVE METHODOLOGY AND ALGORITHMS FOR SOLVING GEOPHYSICAL INVERSE PROBLEMS
Published 2017“…The proposed methodologies and algorithms are based on full-waveform inversion and contribute to this largely unsolved problem. …”
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12
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Article -
13
Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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Monograph -
14
A new high order algorithm with low computational complexity for electric field simulation
Published 2010“…Research efforts to increase the speed of simulating the problem are needed. Approach: Our recent research had found a new method with lower complexity and can simulate the problem faster than the existing FDTD algorithm. …”
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15
A New High Order Algorithm With Low Computational Complexity for Electric Field Simulation
Published 2010“…Research efforts to increase the speed of simulating the problem are needed. Approach: Our recent research had found a new method with lower complexity and can simulate the problem faster than the existing FDTD algorithm. …”
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Citation Index Journal -
16
A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization
Published 2018“…Numerous studies in optimization problems often lead to tailoring a specific algorithm to adapt to the problem instances, especially in expensive optimization problems. …”
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Efficient radio resource management algorithms for downlink long term evolution networks
Published 2018“…The algorithm is based on the idea of the optimization problem in which resource allocation problem is formulated as an optimization problem. …”
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18
Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation
Published 2019“…However, exact algorithms are not feasible for solving complex problem due to its high computational overhead. …”
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Aiding Low Cost Inertial Navigation With Building Heading For Pedestrian Navigation
Published 2024Article -
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Enhannced sampling algorithm in bluetooth low energy for indoor localization
Published 2018“…BLE indoor localizationtechnology able to obtain the position byutilizing the Receive Signal Strength Index (RSSI) which is then used in positioning algorithm such as fingerprinting or trilateration. …”
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