Search Results - intelligence system ((model algorithm) OR (modified algorithm))
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Simulated real-time controller for tuning algorithm using modified hill climbing approach
Published 2014“…That led to new ways to tackle old problems like model inaccuracies and inconsistencies. Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Intelligent surveillance system for street surveillance
Published 2017“…The proposed system is designed to work in real-time. Experimental results show that the proposed background modelling algorithms are able to reconstruct the background correctly and handle illumination and adverse weather that modifies the background. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor
Published 2024“…To simulate the DC motor system with a PI-PD controller that was optimized by several swarm intelligence algorithms, MATLAB/Simulink software was utilized. …”
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Intelligent surveillance system for street surveillance
Published 2017“…The proposed system is designed to work in real-time. Experimental results show that the proposed background modelling algorithms are able to reconstruct the background correctly and handle illumination and adverse weather that modifies the background. …”
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EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency
Published 2016“…A modified Viterbi, a machine-learning algorithm, is used to generate the most probable psychiatric state sequence based on such observations; then, from the most likely psychiatric state sequence, the emergency psychiatric state is predicted through the proposed algorithm. …”
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A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali
Published 2015“…In this thesis, we implement the modified ant colony programming (ACP) algorithm for solving the matrix Riccati differential equation (MRDE). …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Development of a robust intelligent controller for a semi-active car suspension system
Published 2022“…Semi-active suspension systems outperformed passive and active suspension systems because it contains an intelligent actuator that can give the appropriate force to dissipate unwanted vibration using intelligent and real-time controllers. …”
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Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System
Published 2019“…This study first focuses on modifying the PMU model for standard test systems in a MATLAB Simulink environment. …”
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Reactive memory model for ant colony optimization and its application to TSP
Published 2014“…The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model.Based on the results, Max-Min Ant System has been chosen as the base for the modification.The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.…”
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Interactive design psychology and artificial intelligence-based innovative exploration of Anglo-American traumatic narrative literature
Published 2022“…First, by studying natural language processing (NLP) technology, this study proposes a modification language model (LM) based on the double-layered recurrent neural network (RNN) algorithm and constructs an intelligent language modification system based on the improved LM model. …”
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
Published 2025“…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”
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A preliminary lightweight random forest approach-based image classification for plant disease detection
Published 2022“…In this study, we modified the structure of, RF model to improve the overall accuracy and accessibility, to transform it into a lightweight detection system. …”
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
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