Search Results - (( parameter simulation based algorithm ) OR ( pattern generation based algorithm ))
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Computational dynamic support model for social support assignments around stressed individuals among graduate students
Published 2020“…The computational models that simulate support providers and recipients behaviours were developed to generate several simulated patterns. …”
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Thesis -
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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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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Bio-inspired snake robot locomotion: a CPG-based control approach
Published 2015“…In line with this concept, an artificial control system is known as Central Pattern Generator (GPG) is an online motion generation system that can be generated instantly like spine based control system. …”
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Proceeding Paper -
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A Sensorless Positioning System For Linear Dc Motor
Published 2008“…The equation of motion for LDM is then simulated using Matlab software. The time response of the system based on simulation results has been studied and proper adjustment to control parameters has been made to improve the rise time, overshoot percentage and steady state error. …”
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Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network
Published 2024“…The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. …”
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Article -
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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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“…As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. These operational rules were based on the reservoir with a multi-purpose objective: hydropower and intrusion of saltwater. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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Undergraduates Project Papers -
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Water level predictio for Limbang basin using multilayer perceptron (mlp) and radial basis function (rbf) neural network
Published 2010“…Further, strength and limitations of the ANN are discussed, based on the results attained in this study.…”
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Final Year Project Report / IMRAD -
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…Our algorithm works based on prime factorization, and is called Frequent Pattern-Prime Factorization (FPPF).…”
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Conference or Workshop Item -
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…It then divides the compressed database into a set of conditional databases (a special kind of projected database), each associated with one frequent item or pattern fragment, and mines each such database separately.For a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution.In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well.Our algorithm works based on prime factorization, and is called Frequent Pattern- Prime Factorization (FPPF).…”
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Conference or Workshop Item -
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…The optimal simulation parameters can be used for the real application. …”
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Article -
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Using unique-prime-factorization theorem to mine frequent patterns without generating tree
Published 2011“…In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
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PSAT : a pairwise test data generation tool based on simulated annealing algorithm
Published 2015“…This research is about the research on developing a Pairwise Test Data Generation Tool based on Simulated Annealing (SA) algorithm which named as PSAT. …”
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Undergraduates Project Papers -
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…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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