Search Results - (( evolution optimization path algorithm ) OR ( using active sensor algorithm ))
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking
Published 2024“…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim
Published 2007“…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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Differential evolution optimization for constrained routing in Wireless Mesh Networks
Published 2014“…This solution addresses efficient and optimal routing path construction for cost and quality metrics of the application. …”
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Literature Review of Optimization Techniques for Chatter Suppression In Machining
Published 2011“…Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators
Published 2024“…By integrating the ABC algorithm into the manipulator's control system, the goal is to enhance its ability to plan paths and optimize trajectories. …”
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Activity recognition based on accelerometer sensor using combinational classifiers
Published 2015“…Activity recognition using various smartphone sensors can be considered as a one of the crucial tasks that needs to be studied. …”
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Efficient k-coverage scheduling algorithms for wireless sensor networks / Ahmed Abdullah Saleh Al-Shalabi
Published 2014“…Each sensor uses the least possible sensing range to provide coverage, without affecting the network k-coverage; on the other hand, the activated sensors are able to cover the same area, if the operational sensors are activated with their maximum sensing range. …”
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Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin
Published 2013“…This mechanism is restricted to search the possible solutions in a critical path. Modification on the path by using neighborhood search significantly reduces the total length of the makespan. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection systems. …”
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Activity Recognition Based On Accelerometer Sensor Using Combinational Classifiers
Published 2015“…Activity recognition using various smartphone sensors can be considered as a one of the crucial tasks that needs to be studied. …”
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Internet of Things (IoT) based activity recognition strategies in smart homes: a review
Published 2022“…This technique is challenged by the nature of IoT technology and perceived data, as well as by human differences, which necessitated additional processing tasks to select significant features for the learning algorithms. In this work, we focus our review on activity recognition implementation strategies by examining various sensors and sensing technologies used to collect useful data from IoT devices, reviewing preprocessing and feature extraction techniques, as well as classification algorithms used to recognize human activities in smart homes. …”
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On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks
Published 2024“…In the case study, many algorithms have been proposed in the literature, in order to find the maximum number of disjoint or non-disjoint sets of sensor cover sets, we can see where one set can be active at any one time. …”
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A secure trust aware ACO-Based WSN routing protocol for IoT
Published 2022“…The performance of the proposed routing algorithm is demonstrated through MATLAB. Based on the proposed system, to find the secure and optimal path while aiming at providing trust in IoT environment, the average energy consumption is minimized by nearly 50% even as the number of nodes has increased, as compared with the conventional ACO algorithm, a current ant-based routing algorithm for IoT-communication, and a present routing protocol RPL for IoT.…”
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Path Planning and Control of Mobile Robot in Road Environments using Sensor Fusion and Active Force Control
Published 2018“…The sensor fusion algorithm is used to remove noises and uncertainties from sensors' data and provide optimum measurements for path planning. …”
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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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Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…In addition, since smartphones are available to a wide group of people, a low-cost solution for human activity identification can be realized, without requiring the use of external sensors and circuitry.…”
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