Search Results - (( java location based algorithm ) OR ( network solution using algorithm ))
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Friendship Degree and Tenth Man Strategy: A new method for differentiating between erroneous readings and true events in wireless sensor networks
Published 2023“…The second stage will validate the voting process through a novel perspective based on the TMS. TMS will check the voters’ replies based on the event’s location. …”
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Loss reduction in distribution networks using new network reconfiguration algorithm
Published 1996“…The first stage of this solution algorithm finds a loop which gives the maximum loss reduction in the network. …”
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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Group formation using genetic algorithm
Published 2009“…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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Monograph -
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Loss reduction in distribution networks by network reconfiguration: a two stage solution approach
Published 2004“…The first stage of this solution algorithm finds a loop, which gives the maximum loss reduction in the network. …”
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Multi-floor indoor location estimation system based on wireless local area network
Published 2007“…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…An integrated solution for the above problem is the ECQ Routing Algorithm. …”
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Fine-tuning approach in metaheuristic algorithm to prolong wireless sensor networks nodes lifetime
Published 2022“…A set of simulations has been performed using MATLAB R2018b on the proposed solution, namely the energy efficient of genetic (EEG) algorithm and has revealed that the solution outperforms the network lifetime and cluster head load of the existing solution.…”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Decentralized traffic signal control for grid traffic network using genetic algorithm
Published 2019“…Besides, the inherent deterministic behavior limits the algorithm to explore the solution space in searching for the optimum traffic solution. …”
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Proceedings -
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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A survey of state of the art: hierarchical routing algorithms for wireless sensor networks
Published 2014“…Many researches have been done to solve this problem or at least find a solution to decrease the energy consumption. One of those solutions is using efficient routing algorithm. …”
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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems
Published 2015“…The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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Attack path selection optimization with adaptive genetic algorithms
Published 2016“…This paper describes our project that has the ultimate goal of providing optimized solutions for enterprise network security. We describe our approach for implementing an optimized security assessment using Genetic Algorithm (GA). …”
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