Search Results - (( parameters optimization based algorithm ) OR ( pattern generation based algorithm ))
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Optimizing Central Pattern Generators (CPG) Controller For One Legged Hopping Robot By Using Genetic Algorithm (GA)
Published 2018“…This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA).To control the one legged hopping robot,a CPG controller is designed and integrated with a conventional ProportionalIntegral (PI) controller.Conventionally,the CPG parameters are tuned manually.But by using this method,the parameters produced are not exactly the optimum parameters for the CPG. …”
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2
A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…The algorithm filtered the expected irrelevant DNA sequences in database from being computed for dynamic programming based optimal alignment process. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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4
Autonomous flight algorithm of a quadcopter sensing system for methane gas concentration measurements at landfill site
Published 2018“…So, this thesis experiments to ascertain the optimal surveying patterns and sensing parameters required to accurately sense methane gas clouds with minimal selfinduced air disturbance. …”
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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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Improved power output forecastingtechnique for effective battery management in photovoltaic system / Utpal Kumar Das
Published 2019“…A PSO-based algorithm is adopted for the appropriate selection of dominated parameters of SVR-based model to achieve better performance. …”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Based on the acquired results, the experiments reveal that the modified word vectors algorithm can effectively alter original LLM-generated word vectors to reflect intended contexts and can outperform baseline scores in contextual text classification tasks. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. …”
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10
River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network
Published 2024“…The performance of the proposed algorithm then will be examined based on statistical indices namely Root-Mean-Square Error (RSME) and Determination Coefficient (R2). …”
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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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ARTIFICIAL NEURAL NETWORK FOR WATER LEVEL PREDICTION IN A RIVER UNDER TIDAL INFLUENCE
Published 2004“…This model generated the highest R Testing of 0.9425 when trained with the scaled conjugate gradient algorithm (trainscg). …”
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Final Year Project Report / IMRAD -
13
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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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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15
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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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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Modelling hourly runoff using ann for sg. Sarawak Kanan Basin
Published 2005“…The performances of the ANNs were evaluated based on the coefficient of correlation, R. The back propagation algorithm was adopted for this study. …”
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Final Year Project Report / IMRAD -
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Water level predictio for Limbang basin using multilayer perceptron (mlp) and radial basis function (rbf) neural network
Published 2010“…MLP is trained with conjugate gradient algorithms, trainscg and RBF with newrb. The optimal model found in this study is the MLP which is using four days of antecedent data with combination of learning rate and number of neurons in the hidden layer of 0.6 and 60. …”
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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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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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