heuristic model selection method
Solving urban transit route design problem using selection hyper-heuristics
... Thirty selection hyper-heuristics combining several known selection and move acceptance methods were tested and applied on a set of bench- mark instances and their performances were compared to determine ...
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A comparative study of the Lasso-type and heuristic model selection methods
... or method of moments) since it shrinks the coefficients of insignificant regressors towards ...the model forecast is ...subset selection techniques based on the information criteria (IC) and step- ...
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Heuristic sequence selection for inventory routing problem
... in heuristic selection ( ¨ Ozcan et al. 2010), Taguchi method for parameters tuning (G¨ um¨ u¸s, ¨ Ozcan, and Atkin 2016), genetic programming for heuristic selection (Nguyen, Zhang, ...
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Feature Selection for Small Sample Sets with High Dimensional Data Using Heuristic Hybrid Approach
... of around 70% on training data (Tables 4 and 6). Although, due to the small number of samples, NN overfits and thereupon, shows a sudden accuracy decrease over the test data. By reducing the number of input features ...
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Pressure Driven Demand and Leakage Simulation for Pipe Networks Using Differential Evolution
... driven model can be applied in hydraulic analysis with- out any mathematical ...co-content model and optimiza- tion process is ...DE model parameters selected are as follows: number of decision ...
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Heuristic ensembles of filters for accurate and reliable feature selection
... evaluation method (PART or ALL) is more reliable when conducting pair-wise comparisons of FS algorithms by concentrating on filter models and by using 10-fold CV with paired ...FS method looked at the test ...
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State-by-state Minimax Adaptive Estimation for Nonparametric Hidden Markov Models
... Such a result is crucial to control the variance of the estimators by a penalty term σ, which is the result we need for the state-by-state selection method. In the case where only the emission densities ...
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Development of Human Resource Assessment and Selection Model for Computer System Design
... TOPSIS method, let us determine the final assessments of the applicants applied for the job position, and carry out ranking of the applicants in accordance with the obtained ...
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A Model Selection-Based Interval-Mapping Method for Autopolyploids
... zontal axis: A1, A3, B1, B2, B3, D1, D2, D3, E1, E2, and E3. proach or marker configurations based on a joint ap- The letters denote the marker configurations: (A) double proach. We have demonstrated that both methods ...
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Research Method for the Selection of Building Materials and a Model Proposal
... the selection of appropriate materials during the design phase, before the ...calculation method is presented that is to be applied to each material and each impact class when calculating a building’s ...
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(V, A) be a network where V= {0, 1, … ,n } is the vertex
... seconds (1 hour) in each subtour elimination iteration (steps 2 – 4). We tried to increase the processing time per iteration to 15,000 seconds but the program terminated before finding a feasible solution (i.e., it never ...
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Component selection and smoothing in smoothing spline analysis of variance models -- COSSO
... Our method will be referred to as the COmponent Selection and Smoothing Operator ...component selection in the ...correct model structure with probability tending to ...spline method ...
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TEACHING OF SCIENCE AT THE SECONDARY SCHOOL LEVEL IN MEGHALAYA: AN ANALYSIS OF THE TEACHING STRATEGIES ADOPTED BY SCIENCE TEACHERS IN THE TEACHING OF SCIENCE
... The Secondary Education (1952-53) observed that secondary education is a complete unit in itself and not merely a preparatory stage; that at the end of this period, a student should be in a position, if he wishes, to ...
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Covariate-Varying Threshold Selection Method in Non-Stationary Generalized Pareto Model
... a method to partition a data set recursively thus permitting a simple predic- tion model to be fitted within each cluster, rep- resented by terminal node or leaf (Loh, ...
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A heuristic model for pedestrian intention estimation
... simple heuristic model of intent on pedestrian-vehicle trajectory data for the first ...a heuristic approach based on the observed positions of the agents over ...The method can predict ...
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Heuristic Model Development For Nifty Trading
... The research paper has concluded the study performance of Heuristic Model with that of Nifty Bees. The research highlights that S&P CNX NIFTY Index movement is clearly downwards from the June, 2009 to ...
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DETERMINANTS METHOD OF EXPLANATORY VARIABLES SET SELECTION TO LINEAR MODEL
... ple in Canada, France, China and India. In turn, the model with the free parameter that has the smallest error relδ 63 ≈ 0.7%, see Table 3, contains variables that represent the number of people in the same ...
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Semiparametric penalty function method in partially linear model selection
... Abstract: Model selection in nonparametric and semiparametric regression is of both theoretical and practical ...cross–validation selection procedure for the choice of both the parametric and ...
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A Heuristic Model for the Development of Production Capabilities
... Various authors ([4], [11], [12] and [15]) claim that the Real Options theory presents the right heu- ristic approach to capability-development process management. Capability is defined as the organiza- tional know-how ...
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A heuristic model for pedestrian intention estimation
... a model that learns a set of features from a database of LIDAR pedestrian trajectories using support vector machines (SVM) and predicts whether or not a pedestrian will cross the ...planning model as the ...
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