Search Results - (( development practical function algorithm ) OR ( data using optimization algorithm ))
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1
Stochastic process and tutorial of the African buffalo optimization
Published 2022“…This paper presents the data description of the African buffalo optimization algorithm (ABO). …”
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Stochastic process and tutorial of the African bufalo optimization
Published 2022“…This paper presents the data description of the African buffalo optimization algorithm (ABO). …”
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3
Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm
Published 2023“…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
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5
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…Particularly, swmcan addresses multi-view data noise using the l1-norm and optimizes the objective function through a novel iterative reweighted method. …”
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Data-driven fractional-order PID controller tuning for liquid slosh suppression using marine predators algorithm
Published 2023“…In response, this study introduces a data-driven fractional-order PID (FOPID) controller designed using the Marine Predators Algorithm (MPA) for suppressing liquid slosh. …”
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Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm
Published 2023“…Thus, this research paper proposed the development of a data-driven fractional-order PID controller based on marine predators algorithm (MPA) for liquid slosh suppression system. …”
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8
Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The methodology encompasses data acquisition, GA program development, SPM technique implementation, and simulation using MATLAB. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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10
Developing an app for streamlined inventory tracking with barcode scanning and load planning optimization
Published 2025“…The application was implemented using React Native for mobile development and Firebase Firestore as the backend database to enable real-time data synchronization, while a binary tree bin packing algorithm was applied to generate efficient cargo loading arrangements. …”
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Final Year Project / Dissertation / Thesis -
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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13
Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons
Published 2018“…The rolling mechanism method is applied to smooth out the dataset based on the antecedent values of the model inputs before being applied to the GM algorithm. The optimization of the input datasets selection was performed using auto-correlation (ACF) and partial auto-correlation (PACF) functions. …”
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Novel reservoir system simulation procedure for gap minimization between water supply and demand
Published 2019“…In this research, an optimization algorithm, namely, the shark machine learning algorithm (SMLA) that has high inertia for obtaining its targets, is proposed that mimics the natural shark process. …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…However, the evaluation function used in the AI is developed based on historical traffic data. …”
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Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli
Published 2023“…This study focuses on using Python for remote sensing data analysis to identify and classify healthy crops. …”
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Student Project -
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Agreement options for negotiation on material location decision of housing development
Published 2020“…It will need the development of trade-off algorithms to analyze value of technical solution in real time. …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Forward model was also involved in the process of defining the objective function. Next, using simulated data together with historical data, objective function will be computed. …”
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Final Year Project -
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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization
Published 2025“…The Grey Wolf Optimizer (GWO) is enhanced using a chaotic map, improving its ability to find the best solutions and achieve faster convergence, resulting in the ICGWO algorithm. …”
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Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin
Published 2024“…Most of those research results varies as it uses different data, different network design, different parameters and optimizing algorithm. …”
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