Search Results - (( using active method algorithm ) OR ( parameter optimization model algorithm ))
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The proposed algorithm is then used to model tyrosine production in Musmusculus (mouse) by using a dataset, the JAK/STAT(Janus Kinase Signal Transducer and Activator of Transcription) signal transduction pathway. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In addition, ACO algorithm has been used for optimization of PID controller parameters to obtain within rated smooth output power of WT from fluctuating wind speed. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…ReliefF can solve the problem of large feature dimension in the existing RKELM. By using clustering method K-Means, we have found the best center point position to calculate Kernel matrix. at last, we have employed Quantum-behaved Particle Swarm Optimization (QPSO) to get the optimal kernel parameter in the proposed model. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…The FFNN training process which is an optimization task to find the optimal controlling parameters (weights and biases) is considered as the main issues in any model performance. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…These kind of activities highly sparsely distributed in the input space which is problematic to be distinguish using traditional classifier model. …”
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Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity
Published 2018“…The proposed algorithm is capable of selecting the optimal feature subsets while improving the recognition of acceleration activity using a minimum number of features. …”
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Evaluation of different control policies of semi-active MR fluid damper of a quarter-car model
Published 2012“…A Semi-active device is used for this purpose because it carries valuable result which maintains the reliability of passive control methods and includes the advantage of the adjustable parameter characteristics of active systems. …”
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Hybrid intelligent methods for parameter identification and load frequency control in power system
Published 2014“…For example, the classical methods for parameter identification (LSE and MLE), the classical methods for LFC (PI, PD and PID) and the intelligent methods (fuzzy logic, neural network, genetic algorithm, and PSO). …”
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Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm
Published 2024“…Third, this work uses IPSO to optimize the initial network parameters of 1DCNN to build IPSO-1DCNN. …”
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Channel Assignment Algorithms in Cognitive Radio Networks: Taxonomy, Open Issues, and Challenges
Published 2016“…The similarities and differences of the algorithms based on the important parameters, such as routing dependencies, channel models, assignment methods, execution model, and optimization objectives, are also investigated. …”
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DEVELOPMENT OF PREDICTIVE MODELS FOR INFINITE DILUTIONACTIVITY COEFFICIENTOF ALCOHOLIN IONIC LIQUIDSUSING GROUP CONTRIBUTION METHOD
Published 2020“…In this work, two van’tHoff models consist of two (Model I) and three parameters (Model II) are used to calculate the value of IDAC using multiple linear regression (MLR) method and optimized by generalized reduced gradient (GRG) non-linear algorithm in order to obtain a similar value from both experimental and predicted data points…”
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Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
Published 2024journal::journal article -
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Dihydroxystearic acid (DHSA) production by in situ hydrolysis based on optimum process parameters of epoxidized palm oil-derived oleic acid (EPOOA) / Mohd Jumain Jalil
Published 2021“…In this model, the method was integrated with genetic algorithm optimization to determine the process model that fit with the experimental data using MATLAB software. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
Published 2015“…Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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