Search Results - (( parameters optimization based algorithm ) OR ( pattern generation using algorithm ))
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1
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
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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3
Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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4
A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…An automaton-based algorithm is used to develop the filtering process proposed. …”
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5
Autonomous flight algorithm of a quadcopter sensing system for methane gas concentration measurements at landfill site
Published 2018“…During the experimentation, accurate methane gas concentration measurements at landfill sites were obtained using the algorithm for autonomous flight, with the implementation of optimal quadcopter flight parameters and gas sensor mounting arrangements. …”
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6
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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7
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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8
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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9
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To bridge this gap, a five-phase research methodology is structured to propose and evaluate an algorithm enabling the external modification of LLM-generated word vectors using scalar values as the focus weightage. …”
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10
Bio-inspired snake robot locomotion: a CPG-based control approach
Published 2015“…This research shows a novel algorithm to generate online sinusoidal motion generation using CPG for planar space. …”
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Proceeding Paper -
11
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 -
12
Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…Furthermore, the efficiency of the proposed algorithm was assessed using some reservoir performance indices such as resilience and reliability. …”
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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“…The architecture of artificial neural network (ANN) laid the foundation as a powerful technique in handling problems such as pattern recognition and data analysis. It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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15
Modelling hourly runoff using ann for sg. Sarawak Kanan Basin
Published 2005“…This model generated the highest R Testing of 0.896 when trained with the scaled conjugate gradient algorithm (TRAINSCG). …”
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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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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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18
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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