Search Results - (( parameter selection based algorithm ) OR ( pattern optimization method algorithm ))

Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
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Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

“…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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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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Improving neural networks training using experiment design approach by Chong, Wei Kean

“…One more data (m+ 1) is entered to train the NN again. This data is selected by two methods: random and Experiment Design Approach (D-optimal and Maxmin Distance). …”
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Derivation of radiative transfer parameters using image-based technique / Wan Noniafida Ab Manan by Ab Manan, Wan Noniafida

“…This study is attempting to answer whether selection of atmospheric models is based on regional atmospheric condition or geographic location. …”
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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

“…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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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…Feature selection techniques, such as WrapperSubsetEval, were used to improve focus on key attributes, and parameter tuning further optimized performance. …”
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Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu by Abdul Mannan, Dadu

“…The switching state pattern is selected according to peak to peak value of CMV and CMV weighting factor is related to peak value of CMV and a user defined co-efficient. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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Application of pattern search method to economic load dispatch with valve point loading / Siti Aisah Md. Sari by Md. Sari, Siti Aisah

“…This study presents the application of Pattern Search (PS) method in Economic Dispatch (ED) problem; ED is used to optimize the fuel cost of electric energy while at the same time allocate the demand between available generation unit. …”
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Sheet C1 Pattern Number Recognition Using Artificial Immune System Optimization by Yuniarti Denita, Sari, Tri Basuki, Kurniawan, Edi Surya, Negara, Tata, Sutabri

“…In order to recognize the numerical patterns on sheet C1, we, therefore, require a method that uses the Artificial Immune System (AIS), specifically the CSA (Clonal Selection Algorithm) algorithm, which is one of the AIS system's algorithms for optimization. …”
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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

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Optimizing Central Pattern Generators (CPG) Controller For One Legged Hopping Robot By Using Genetic Algorithm (GA) by Chong, Shin Horng, Azahar, Arman Hadi, Mohamed Kassim, Anuar, Zainal Abidin, Amar Faiz, Harun, Mohamad Haniff, Nor Shah, Mohd Badril, Mohd Annuar, Khalil Azha, Manap, Mustafa, Rizman, Zairi Ismael

“…Therefore,a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. …”
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Performance optimization on axial-flux permanent magnet coreless generator using novel hybrid computational method based on genetic algorithm and pattern search / Lok Choon Long by Lok , Choon Long

“…Complex real-world problems can be solved by heuristic optimization efficiently. Improved hybrid optimization method using Pattern Search (PS) and Genetic Algorithm (GA) onto Axial-Flux Permanent Magnet (AFPM) Coreless generator is presented in this thesis, and the optimization is based on the popular multi-objective sizing equation. …”
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Using Pattern Search Methods for Minimizing Clustering Problems by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June, Mohagheghtabar, Maryam

“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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Linear array beampattern gain optimization techniques by Nagi F.

“…In the goal attaining algorithm the goal of optimization is set to the reference pattern. …”

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

Planar array failed element(S) radiation pattern correction: A comparison by Boopalan N., Ramasamy A.K., Nagi F., Alkahtani A.A.

“…This paper compares the few available optimization methods, namely, simulated annealing (SA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Pattern Search (PS) methods. …”