Search Results - (( variable selection based algorithm ) OR ( parameter simulation based algorithm ))
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1
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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2
Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria
Published 2021“…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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3
Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria
Published 2021“…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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4
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”
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5
Mobile data gathering algorithms for wireless sensor networks
Published 2014“…The selection of this parameter is based on the application requirements. …”
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6
Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model
Published 2001“…The implementation and the computational aspects of the training algorithm are also highlighted. Three examples of discrete-time nonlinear systems are used in the simulation study to show the effects of user selected conditions on the identification process. …”
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7
Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Furthermore, it enables non-dominated evaluation of solutions based on four objectives using crowding distance for selection. …”
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8
Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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9
Monthly rainfall prediction model of Peninsular Malaysia using clonal selection algorithm
Published 2018“…The proposed Clonal Selection Algorithm (CSA) is one of the main algorithms in AIS, which inspired on Clonal selection theory in the immune system of human body that includes selection, hyper mutation, and receptor editing processes. …”
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10
Parameter Magnitude-Based Information Criterion For Optimum Model Structure Selection In System Identification
Published 2020“…This study presents the comparison between parameter-magnitude based information criterion 2 (PMIC2), PMIC (an earlier version of its kind), AIC and BIC in selecting a correct model on simulated data and real data. …”
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11
Monthly rainfall prediction model of Peninsular Malaysia Using Clonal Selection Algorithm
Published 2023“…The proposed Clonal Selection Algorithm (CSA) is one of the main algorithms in AIS, which inspired on Clonal selection theory in the immune system of human body that includes selection, hyper mutation, and receptor editing processes. …”
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12
Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen
Published 2011“…Based on the evolution of the process dynamics given by the VFF-RLS algorithm in the form of First Order Plus Dead Time (FOPDT) model parameters, the move suppression weight for the AS-GPC was recalculated automatically at every time step based on the analytical tuning expressions. …”
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13
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…The simulation and comparison results indicate the superiority of the proposed algorithm. …”
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14
Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Thus, a safe experimentation dynamics (SED) algorithm is selected to solve this unstable convergence but still not enough to achieve high accuracy because the update designed parameter only depends on the fixed step size gain. …”
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15
Fault diagnostic advisory system using moving-range chart and hazard operability study
Published 2007“…PlantTM simulator. Moving-Range (x-MR) Chart and HAZOP study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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16
Fault diagnostic advisory system using moving-range chart and hazard operability study.
Published 2007“…Although the scheme was developed based on precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP study for each selected monitoring variables.…”
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17
Neural network based adaptive pid controller for shell-and-tube heat exchanger
Published 2019“…The neural network model consists of 4 input variables and 4 output variables. Simulation and development of the controller was done in the Simulink environment meanwhile the effectiveness of the controller was evaluated based on the set point tracking and disturbance rejection. …”
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Neural network based adaptive pid controller for shell-and-tube heat exchanger: article
Published 2019“…The neural network model consists of 4 input variables and 4 output variables. Simulation and development of the controller was done in the Simulink environment meanwhile the effectiveness of the controller was evaluated based on the set point tracking and disturbance rejection. …”
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19
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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20
Penalized LAD-SCAD estimator based on robust wrapped correlation screening method for high dimensional models
Published 2021“…The SIS method uses the rank correlation screening (RCS) algorithm in the pre-screening step and the traditional Pathwise coordinate descent algorithm for computing the sequence of the regularization parameters in the post screening step for onward model selection. …”
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