Search Results - (( data optimization method algorithm ) OR ( systems implementation learning algorithm ))
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Multi-Robot Learning with Bat Algorithm With Mutation (Bam)
Published 2022“…Multiple techniques like swarm optimization, cuckoo algorithm and other such algorithms are under study for multi robotic systems. …”
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Undergraduates Project Papers -
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting
Published 2025“…The proposed method achieved superior forecasting accuracy compared to benchmark algorithms including standard teaching-learning-based optimization with extreme learning machine, manta rays foraging optimization with extreme learning machine, moth flame optimization with extreme learning machine, ant colony optimization with extreme learning machine and salp swarm algorithm with extreme learning machine. …”
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Article -
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Student Project -
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A fast learning network with improved particle swarm optimization for intrusion detection system
Published 2019“…This situation makes the detection of cyber-based attacks on computer networks a relevant and challenging area of research. The Fast Learning Network (FLN) is one of the new machine learning algorithms that are easy to implement, computationally efficient, and with excellent learning performance characteristics. …”
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Thesis -
5
A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine
Published 2025“…The numerical experimental results demonstrated that the ABWO algorithm beat all other optimization methods and could solve the majority of the benchmark functions. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Thesis -
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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9
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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10
Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…Several researchers have reported different optimization methods for blade parameters such as Blade Element Momentum theory (BEM), Computational Fluid Dynamics (CFD) and Supervisory Control and Data Acquisition (SCADA) system. …”
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Thesis -
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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Book Section -
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Automated traffic counting data collection and analysis
Published 2021“…There have been many methods of traffic data collection proposed and implemented over the years, each with their own pros and cons. …”
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Final Year Project / Dissertation / Thesis -
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A Constrained Optimization based Extreme Learning Machine for noisy data regression
Published 2023“…Artificial intelligence; Benchmarking; Data handling; Knowledge acquisition; Lagrange multipliers; Learning systems; Optimization; Regression analysis; Benchmark data; Constrained optimization methods; Data regression; Extreme learning machine; Kernel function; Noisy data; Optimization problems; Support vector regression (SVR); Constrained optimization; nitric oxide; algorithm; Article; artificial intelligence; artificial neural network; classifier; combustion; entropy; exhaust gas; extreme learning machine; fuzzy system; generalized regression neural network; generalized regression neural network and fuzzy art; housing; kernel method; logistic regression analysis; machine learning; Malaysia; priority journal; probabilitistic entropy based neural network; process optimization; radial based function; regression analysis; support vector machine…”
Article -
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Deep Reinforcement Learning For Control
Published 2021“…However, determining the essential behavioral outputs for autonomous driving vehicle systems or selecting the optimal output features to learn from them is not easy. …”
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Monograph -
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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Conference or Workshop Item -
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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Thesis -
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Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs
Published 2015“…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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Article -
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Kernel methods and support vector machines for handwriting recognition
Published 2023“…Finding the solution hyperplane involves using quadratic programming which is computationally intensive. Algorithms for practical implementation such as sequential minimization optimization (SMO) and its improvements are discussed. …”
Conference paper -
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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