Search Results - (( model evaluation path algorithm ) OR ( using optimization path algorithm ))

A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…These algorithms generate paths using random numbers and perform efficiently in guiding the robot in known environments. …”
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed by Aneesa Ali, Ali Saeed

“…A model-driven approach was used for generating abstract test cases from the feasible paths. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm by Abu Samah, Khyrina Airin Fariza

“…Through ST adaptation, all subsystems were integrated and using the “Dijkstra’s algorithm” (DA) by modifying its function from shortest path algorithm to safest and shortest algorithm, to the nearest exit. …”
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Transmission path optimization Based on Efficiency Communication System by Jin Fan, Kit, Guan Lim, Sin, Helen Ee Chuo, Min, Keng Tan, Ali Farzamnia, Tze, Kenneth Kin Teo

“…This paper points out the research focus of the wireless sensor network transmission path and discusses the optimization problem of the transmission based on grid model. …”
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Solving the optimal path planning of a mobile robot using improved Q-learning by Low, Ee Soong, Ong, Pauline, Cheah, Kah Chun

“…Additionally, the effectiveness of the proposed algorithm is validated in a real-world experiment using a three-wheeled mobile robot.…”
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Path Following Using A Learning Neural Network by NHH , Mohamad Hanif

“…The implemented neural controller will in turn minimize a performance index, which includes the lateral and attitude angle errors ofvehicle models with respect to the paths. The thesis differs from [2] in a sense that different types of neural controller are established to achieve a better path following accuracy. …”
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Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm by Muhamad Rozikin, Kamaluddin, M. F. F., Ab Rashid

“…This paper used a well-known metaheuristic optimization method, Particle Swarm Optimization (PSO) for solving AVRP models. …”
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Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

“…The present algorithm exhibits attractive features such as high optimality, high stability, low running cost and zero failure rates. …”
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Workload performance evaluation of large spatial database for DSS based disaster management by Rohman, Muhammad Syaifur

“…Data recorded in the shortest path analysis process reveals that the evaluation and the prediction on workload performance of shortest path analysis using Dijkstra algorithm has been well implemented. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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Trust-based enhanced ACO algorithm for secure routing in IoT by Sharmin, Afsah, Motakabber, S M A, Hassan Abdalla Hashim, Aisha

“…In order to provide an energy-efficient and secure routing method for sensors deployed within a dynamic IoT network, this paper presents a trust-aware enhanced ant colony optimization (ACO)-based routing algorithm, incorporating a lightweight trust evaluation model. …”
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Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network by Tareq, M., Abed, S.A., Sundararajan, E.A.

“…Hence, emphasizing the need to establish an efficient connection inside the network we use for a routing protocol to explore paths among nodes. …”
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Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

“…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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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Collision avoidance mechanisms using artificial potential field for UAVs by Abdul Azis, Fadilah, Tan, Jie Sim, Md Ghazaly, Mariam, Mohamad Hanif, Noor Hazrin Hany

“…To evaluate algorithmic performance, three simulated scenarios were developed: (i) varying obstacle densities, (ii) extreme goal positioning, and (iii) external wind disturbances. …”
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Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

“…Two case studies are used to evaluate those algorithms, and the camera placement problem is formulated as a coverage maximization problem. …”
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Solving vehicle routing problem by using improved genetic algorithm for optimal solution by Mohammed M.A., Abd Ghani M.K., Hamed R.I., Mostafa S.A., Ahmad M.S., Ibrahim D.A.

Accurate range free localization in multi-hop wireless sensor networks by Abdulwahhab, Abdullah Raed

“…Simulation and experimental results show a substantial performance gain achieved by our proposed localization algorithm in wireless sensor networks. The performance is evaluated in terms of RMSE in terms of three algorithms WLS, CRLR, and GMSDP based on using the Monte Carlo simulation with account the number of anchors that varying from anchor=4 to anchor =20. …”
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