Search Results - (( parameter optimization based algorithm ) OR ( variable interactions _ algorithm ))
Search alternatives:
- parameter optimization »
- variable interactions »
-
1
CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm
Published 2019“…To overcome the combinatorial optimization problem, Jaya algorithm is proposed to apply in this project since metaheuristic algorithm is fast in optimization and this strategy is named as CTJ. …”
Get full text
Get full text
Get full text
Undergraduates Project Papers -
2
Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
Get full text
Get full text
Get full text
Book Chapter -
3
Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…The existing data-driven neuroendocrine-PID (NEPID) utilizes the simultaneous perturbation stochastic approximation (SPSA) algorithm as the data-driven tool. However, this SPSA-based method is unable to find the optimal value of the design parameter due to unstable convergence obtained that degrades the controller performance in MIMO systems. …”
Get full text
Get full text
Thesis -
4
CTJ: Input-output based relation combinatorial testing strategy using Jaya algorithm
Published 2019“…In this paper, a Jaya algorithm is proposed as an optimization algorithm engine to construct a test list based on IOR in the proposed combinatorial test list generator strategy and named as (CTJ). …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
5
HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation
Published 2021“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
Get full text
Get full text
Article -
6
HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation
Published 2021“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
Get full text
Get full text
Article -
7
HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
Get full text
Get full text
Article -
8
HABC: Hybrid artificial bee colony for generating variable T-way test sets
Published 2020“…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
Get full text
Get full text
Article -
9
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…The synthetic reaction was optimized by Taguchi method based on orthogonal array to evaluate the effect of each parameters and interactive effects of reaction parameters including temperature, time, amount of enzyme, amount of molecular sieve, amount of solvent, and molar ratio of substrates (xylitol: fatty acid). …”
Get full text
Get full text
Thesis -
10
Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…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. …”
Get full text
Get full text
Get full text
Thesis -
11
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
Get full text
Get full text
Get full text
Thesis -
12
Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012Get full text
Get full text
Conference or Workshop Item -
13
Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence
Published 2019“…During the optimization process, the decision variables were represented by four different operating parameters. …”
Get full text
Get full text
Article -
14
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
Get full text
Get full text
Conference or Workshop Item -
15
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. …”
Get full text
Get full text
Thesis -
16
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.…”
Get full text
Get full text
Get full text
Article -
17
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
Get full text
Get full text
Thesis -
18
Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
Get full text
Get full text
Thesis -
19
Identification of debris flow initiation zones using topographic model and airborne laser scanning data
Published 2017“…Conditioning parameters were numerically optimized to identify the arbitrarily maximum model basis function for eleven variables, using MARSplines analysis (algorithm). …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
20
LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
Published 2015Get full text
Get full text
Get full text
Conference or Workshop Item
