Search Results - (( variable interactions based algorithm ) OR ( variable estimation using algorithm ))
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1
A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling
Published 2009“…This paper presents the application of Parallel Genetic Algorithm (PGA)-based Takagi Sugeno Kang (TSK)-Fuzzy approach for dynamic car-following modeling in the traffic simulation software. …”
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2
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…A modeling approach is developed which focuses on the phases in the model-building procedures, effects of interactions variables on the model, minimizing the effects of multicollinearity on the variables and recommending remedial techniques to overcome them, identification of the significant variables by removing insignificant variables, selecting the best model using the eight selection criteria (8SCs), and finally using the residual analysis to validate the chosen best model. …”
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3
Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…The proposed feature selection technique comprises of Multi-objective Binary-valued Backtracking Search Algorithm (MOBBSA). It is used to search within a number of input variables combinations and to select the feature subsets, which minimizes simultaneously vice-versa the estimation error and the feature numbers. …”
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4
Modelling the yield loss of oil palm due to Ganoderma Basal Stem Rot disease
Published 2016“…For estimation-post-selection approach, there were two subset selection algorithms were applied, namely backward stepwise subset selection and best-subset selection. …”
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5
Modelling the yield loss of oil palm due to ganoderma basal stem rot disease
Published 2016“…For estimation-post-selection approach, there were two subset selection algorithms were applied, namely backward stepwise subset selection and best-subset selection. …”
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6
SOFT SWITCHING SYSTEM BASED ON WEIGHTED PROBABILITIES FOR STOCHASTIC HYBRID MULTIPLE MODEL-BASED CONTROL SYSTEMS
Published 2010“…Stochastic hybrid model-based control refers to controlling uncertain systems, which are modeled as a multiple-model set with a varying variable structure and the use of interacting multiple model (IMM) estimator and generalized predictive control (GPC) algorithm as described in [1]. …”
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7
Soft Switching System Based on Weighted Probabilities for Stochastic Hybrid Multiple Model-based Control Systems
Published 2010“…Stochastic hybrid model-based control refers to controlling uncertain systems, which are modeled as a multiple-model set with a varying variable structure and the use of interacting multiple model (IMM) estimator and generalized predictive control (GPC) algorithm as described in [1]. …”
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8
A new estimation of nonlinear contact forces of railway vehicle
Published 2021“…The purpose of this paper is to develop a model-based estimation technique using the Extended Kalman Filter (EKF) with inertial sensors to estimate non-linear wheelset dynamics in variable adhesion conditions. …”
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9
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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10
Evolutionary approach for combinatorial testing of software product lines
Published 2020“…The approaches are (1) adopting an Estimation of Distribution Algorithm approach to aid the construction of a covering array driven by second order feature dependence, and (2) construct a feature configuration dependence graph to assist in building the variable-strength covering array. …”
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11
Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption
Published 2015“…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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12
Grid-based remotely sensed hydrodynamic surface runoff model using emissivity coefficient / Jurina Jaafar
Published 2015“…The process from the satellite information allows an optimal judgment to decide the most appropriate Manning roughness to be used in the simulation of surface runoff. The algorithm is applied the Sungai Pinang and Sungai Dondang river basin. …”
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13
Identification of debris flow initiation zones using topographic model and airborne laser scanning data
Published 2017“…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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14
Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property
Published 2013“…The best set of parameters that could produce more accurate results in the validation process, were selected and their associated neighbourhood and weights were used to compare with the linear models. The experiments were replicated on three different treatments based on removal of outliers and transformation of variables with high value of skewness. …”
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15
A variable combinatorial test suite strategy based on modified greedy algorithm
Published 2015“…This proposed will suggest a new CIT strategy based on a modified greedy algorithm (MGA) with addressing the supporting of variable strength interaction to generate a satisfactory test suite size.…”
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16
Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…The fixed block matching uses the same block size throughout the motion estimation process while the variable block matching uses different block size. …”
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17
A new variable strength t-way strategy based on the cuckoo search algorithm
Published 2019“…Complementing existing works, this paper proposes a new variable strength cuckoo search algorithm, called VCS. …”
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18
Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…Therefore, the main objective of this study is to improve the validity and reliability of the simplified biofilm growth model to optimize the laboratory MEC process of biohydrogen production from sago wastewater substrate using MATLAB. Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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19
Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
Published 2011“…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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20
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The reweighted fast, consistent and high breakdown (RFCH) estimator is a multivariate procedure used to estimate the robust location and scatter matrix. …”
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