Search Results - (( parameter adaptation force algorithm ) OR ( java simulation optimization algorithm ))
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1
Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms
Published 2001“…These parameters are adaptively computed on-line while the robot is executing a trajectory tracking task and subject to some forms of external disturbances. …”
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2
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong
Published 2004“…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. Two iterative learning algorithms are employed in the study - the first is used to tune automatically the controller gains while the second to estimate the inertia matrix of the robotic arm. …”
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4
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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6
Crowd behavior monitoring using self-adaptive social force model
Published 2019“…The obtained new locations for all the particles are necessary in estimating the interaction force of each particle. The combination of psychological and physical parameters in Self-Adaptive SFM makes it more realistic and mimicked the dynamic motion of people in a crowd. …”
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Adaptive impedance control for unknown non-flat environment
Published 2013“…The force error feedback is utilized in the estimation and the accurate knowledge of the environment parameters are not required by the algorithm. …”
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An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization
Published 2019“…In this study, a complete solution to the two scenarios through an adaptive algorithm switching strategy is explored. …”
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9
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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11
Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm
Published 2025“…The intent is to formulate an algorithm capable of adapting to fluctuations in excitation frequencies and the structural modal parameters. …”
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Sensitivity analysis of drill wear and optimization using Adaptive Neuro fuzzy –genetic algorithm technique toward sustainable machining
Published 2018“…Effects of spindle rotational speed, feed rate and diameter of drill on tool wear were determined through Adaptive Neuro Fuzzy Inference System (ANFIS). Next, genetic algorithm (GA) was used to identify the optimal drilling parameter for different diameters of drill. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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14
Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique
Published 2022“…The work in this thesis is expected to be the best approach in formulating an adaptive fuzzy technique based on brute force and regression algorithms for optimization and prediction of EMS in BEV application.…”
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…A new mutation vector inspired by the two-opposite path (2-Opt) algorithm with adaptive mutation scalar (F ) and crossover rate (CR) control parameters were employed to enhance the exploration and exploitation phases of the proposed algorithm. …”
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20
A new terminal sliding mode control for bridge cranes
Published 2021“…Specifically, the bridge crane model is changed first, and then a suitable non-singular terminal sliding surface is selected. The adaptive rate is introduced in the design of the controller, so that the driving force is continuous and does not require information of system parameters. …”
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