Search Results - (( parameter optimization system algorithm ) OR ( pattern optimization method algorithm ))
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…This proposal discusses the techniques of optimizing and deploying machine learning algorithms on embedded devices for manufacturing applications; We investigate problems of printed circuit board (PCB) defects and artificial intelligence in embedded system. …”
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Final Year Project / Dissertation / Thesis -
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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique
Published 2022“…The vehicle was configured according to backward facing model and the design incorporated the technical specifications of a Malaysia local car, PROTON IRIZ (BEV). An optimal solution was proposed by integrating fuzzy logic technique with brute force algorithm that gave the best system optimization, where the decision was based on the Satisfaction Ratio (SR) and State of Charge (SoC). …”
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Thesis -
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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks
Published 2017“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Thesis -
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…The results indicated that the hydropower generated by the proposed algorithm could produce an evenly distributed high amount of energy increases the reliability of the reservoir system. …”
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Thesis -
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Computational dynamic support model for social support assignments around stressed individuals among graduate students
Published 2020“…Hence, this study aims to develop the dynamic configuration algorithm to provide an optimal support assignment based on information generated from both social support recipient and provision computational models. …”
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Thesis -
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab
Published 2025“…The research improved the predictive models by integrating them with the Genetic Algorithm (GA). The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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Thesis -
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Case study : an effect of noise in character recognition system using neural network
Published 2003“…These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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Conference or Workshop Item -
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Thesis -
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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Thesis -
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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin
Published 2011“…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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Thesis -
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…On the other hand, consideration of all parameters in an APP model makes the generation of a master production schedule deeply complicated especially in real-world APP problems, where input data or parameters are frequently imprecise (fuzzy) due to incomplete or un obtain able information and daily changes patterns of demand and manufacturers capacity (Sakalhet al., 2010). …”
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Analysis and decentralised optimal flow control of heterogeneous computer communication network models
Published 1993“…The maximum number of packets in transit within the system corresponding to a maximum throughput and can be determined from a preassigned upper bound on the mean time delay, the average allowed load and the parameters of the underlying systems. …”
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Bio-inspired snake robot locomotion: a CPG-based control approach
Published 2015“…To optimize the CPG parameters, for the optimum output signals, particle swarm optimization (PSO) is applied in this paper. …”
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Proceeding Paper -
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Modified Seird model: a novel system dynamics approach in modelling the spread of Covid-19 in Malaysia during the pre-vaccination period
Published 2023“…This study implemented the preliminary stage of forecasting the COVID-19 data using the proposed SEIRD model and highlighted the importance of parameter optimization. The mathematical model is solved numerically using built-in Python function ‘odeint’ from the Scipy library, which by default uses LSODA algorithm from the Fortran library Odepack that adopts the integration method of non-stiff Adams and stiff Backward Differentiation (BDF) with automatic stiffness detection and switching. …”
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