Search Results - (( probable optimization method algorithm ) OR ( numerical optimization sensor algorithm ))
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…Furthermore, variable switching times are known to cause problems in the implementation of any numerical algorithm due to the variable location of discontinuities in the dynamics. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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Global optimization method for continuous - Time sensor scheduling
Published 2010“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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Adaptive Algorithm for Optimal Route Configuration in Multi-Hop Wireless Sensor Network
Published 2017“…This paper proposes an optimal route configuration technique based on an adaptive genetic algorithm in which the architecture of multi-hop wireless sensor network is considered as a distributed computing infrastructure. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Ant colony optimization for controller and sensor-actuator location in active vibration control
Published 2013“…The main focus of this paper is to find the optimal location of the collocated sensor-actuator and controller gains to actively control vibration, using a swarm intelligent algorithm called Ant Colony Optimization (ACO) and verified with Genetic Algorithm (GA). …”
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Proceeding Paper -
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Unequal clustering by improved particle swarm optimization in wireless sensor network
Published 2015“…The performance of the adopted IPSO algorithm are validated by Numerical experiments in conventional background, however it has not been deployed in cluster-based WSNs which is done by this research. …”
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ANT colony optimization for controller and sensor-actuator location in active vibration control
Published 2013“…The main focus is to find the optimal location of the collocated sensor-actuator and controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Ant colony optimization for controller and sensor-actuator location in active vibration control
Published 2013“…The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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A proposed genetic algorithm to optimize service restoration in electrical networks with respect to the probability of transformers failure
Published 2010“…In many researches a Genetic Algorithm is employed as a powerful tool to solve this multi-objective, multi-constraint optimization problem. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…This study developed an optimized variation of the DV-Hop localization algorithm for anisotropic wireless sensor networks. …”
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14
Whale optimization algorithm strategies for higher interaction strength t-way testing
Published 2022“…To ensure that WOA conquers premature convergence and avoids local optima for large search spaces (owing to high-order interaction), three variants of WOA have been developed, namely Structurally Modified Whale Optimization Algorithm (SWOA), Tolerance Whale Optimization Algorithm (TWOA), and Tolerance Structurally Modified Whale Optimization Algorithm (TSWOA). …”
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Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study
Published 2017“…Also, the clustering approaches support the scalability of Wireless Sensor Networks. In this paper, numerous energy efficient routing algorithms for hierarchical routing protocol in Wireless Sensor Networks have been discussed based on the clustering approaches. …”
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. Also, convergence in the probability function of employee bees’ movement was prevented by increasing the number of route-creating tours. …”
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Optimal forwarding routing protocol in ipv6-based wireless sensor network
Published 2009“…Normally, these applications require numerous low cost, low power and low data sensor nodes that communicating over multiple hop to cover a large geographical area. …”
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Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
Published 2016“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz
Published 2016“…Therefore, optimization methods are often used in the sizing algorithms for such systems. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm as population-based methods are better identifying promising areas in the search space, while Tabu Search and Simulated Annealing as trajectory methods are better in exploring promising areas in search space. …”
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