Search Results - weight optimization ((((method algorithm) OR (sensor algorithm))) OR (path algorithm))
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1
Modelling of multi-robot system for search and rescue
Published 2023“…Moreover, to cope with dynamic environments, a combination of global and local path planning methods is introduced. The PSO algorithm functions as a global path planner, determining the complete path for each robot, whereas a sensor-based obstacle avoidance algorithm serves as a local planner to avoid collision with dynamic obstacles during navigation. …”
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2
Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…This study investigated the implementation and comparison between well known shortest path method which are Dijkstra’s algorithm, Bellman-Ford, and A* algorithm. …”
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3
Comparative Study of Weighted Product–Dijkstra’s Algorithm and All Possible Path Approach Based on Multiple Criteria and Multi-Dimensions
Published 2020“…It was a combined algorithm of Weighted Product Method (WPM) and Dijkstra’s Algorithm. …”
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4
Design of radix-4 single path delay fast fourier transform processor with genetic algorithms optimization
Published 2011“…The genetic algorithms is proven to be a very effective method in optimization by using the way imitating natural process of living beings such as crossover, mutation and selection. …”
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5
A trust aware secure ant colony optimization based routing algorithm for Internet of Things
Published 2023“…For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. …”
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Proceeding Paper -
6
High Rise Building Evacuation Route Model Using DIJKSTRA'S Algorithm
Published 2015“…As a result, the evacuation route model is able to gain the shortest path and safest path consistently between Dijkstra’s algorithms and hybrid version which is Dijkstra-Ant Colony Optimization (DACO). …”
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7
An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…Both algorithms are compared. Simulation is used as a method in this study. …”
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8
Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim
Published 2007“…This approach solves the single-source shortest path problem with nonnegative edge weights. In this paper, GA has been applied to find the minimum path, then result will be compared with Dijkstra's algorithm are presented.…”
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9
Optimised multi-robot path planning via smooth trajectory generation
Published 2024“…Particle swarm optimization (PSO) outperforms conventional methods like artificial potential fields (APF), the Dijkstra algorithm, and the A* algorithm in path planning for mobile robots. …”
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Final Year Project / Dissertation / Thesis -
10
Test case minimization applying firefly algorithm
Published 2018“…The proposed test case minimization method has the following steps: provide weight to the paths, calculate path coverage for each path, transform an immediate graph into an adjacency matrix, which later is used to apply firefly algorithm and generate optimal test cases. …”
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Article -
11
Improvement and application of particle swarm optimization algorithm
Published 2025“…This method combines CPTD with the Genetic Algorithm and PSO (GAPSO), resulting in an effective strategy for dynamic formation reconfiguration and path optimization. …”
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12
Path Following Using A Learning Neural Network
Published 2004“…Two algorithms, gradient descent and quasi-Newton which utilize a batch training method, are introduced as comparison to the gradient descent method that incorporates the online (or incremental) training method. …”
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Final Year Project -
13
Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
Published 2023“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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14
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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15
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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16
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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17
Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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18
Speed sensorless control of permanent magnet synchronous motor using model reference adaptive system and artificial neural network / Abdul Mu’iz Nazelan
Published 2019“…This study introduced a new method to train the HMLP network using PSO algorithm. …”
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19
An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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RWP-NSGA II: reinforcement weighted probabilistic NSGA II for workload allocation in fog and internet of things environment
Published 2024“…This study investigates workload allocation in the IoT node and the fog nodes by optimizing delay and energy consumption. This paper proposes an improved version of NSGA II, namely, reinforcement weighted probabilistic NSGA II, which uses weighted probabilistic mutation. …”
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