Search Results - (( variable optimization techniques algorithm ) OR ( parameter adaptation path algorithm ))
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1
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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2
Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…In autonomous robot design, the main problem faced by researchers is the path planning of mobile robot. Various kind of path planning algorithm was introduced in the past, but no algorithm has absolute superior towards the others algorithm. …”
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Proceedings -
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Attack path selection optimization with adaptive genetic algorithms
Published 2016“…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
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4
Attack path selection optimization with adaptive genetic algorithms
Published 2016“…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
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5
Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments
Published 2013“…This paper presents a new scheme for RRT*-Smart that helps it to adapt to various types of environments by tuning its parameters during planning based on the information gathered online. …”
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6
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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Research Report -
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Minimization of tool path length of drilling process using particle swarm optimization (PSO)
Published 2020“…For this study, the main purpose is to apply the Particle Swarm Optimization (PSO) algorithm for use in searching for the optimal tool routing path for in simulation of drilling process…”
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Book Section -
10
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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11
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. …”
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Efficient multi-UAV coordination via rl: joint path planning and task scheduling for post-disaster UAV-assisted MEC systems
Published 2025“…In this paper, we propose the Geometric Reinforcement Learning Algorithm (GRLA), a unified framework for joint path planning and task scheduling in multi-UAV MEC systems. …”
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Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network
Published 2020“…The proposed Quality of Path QoP metric is incorporated into the modified relay selection algorithm, which improves the efficiency of relay selection mechanism to find optimal path with high link quality. …”
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14
A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…The ACO algorithm in the Bluetooth M-LPNWSN system reduces energy consumption by 60% over 500 iterations and significantly improves data delivery rates by adapting dynamically to network topology and traffic. …”
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15
An adaptive predictive fuzzy logic for the altitude control of a micro-satellite
Published 2010“…The predictor estimates the required control at the next sampling time and applies to the system at the current sampling time. The adaptive portion of FLC compensates the effect of unknown variations of parameters in the satellite system by using an adaptable gain is connected in the forward path of the FLC. …”
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Multi agent quality of service routing based on scheme ant colony optimization algorithm
Published 2014“…This study also introduces a new probe-based procedure for discovery and setup QoS path for real-time traffic. The proposed scheme has been simulated by OMNET++ and compared with standard AntNet and two well-known standard QoS routings; Widest Shortest Path (WSP) algorithm and Shortest Widest Path (SWP) algorithm. …”
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Mixed variable ant colony optimization technique for feature subset selection and model selection
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Conference or Workshop Item -
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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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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…(i) what decision making models and (ii) what computational techniques, provide an optimal manufacturing process planning solution in a multidimensional decision variables space? …”
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