Search Results - (( probable estimation methods algorithm ) OR ( ii optimization method algorithm ))
Search alternatives:
- probable estimation »
- estimation methods »
- methods algorithm »
- method algorithm »
- ii optimization »
-
1
Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
Get full text
Get full text
Get full text
Thesis -
2
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
Get full text
Get full text
Thesis -
3
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
4
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Due to the effective attraction-repulsion mechanism of electromagnetic-like (EM) algorithm and reliable exploration and exploitation phases of differential evolution (DE), these two methods were used to determine parameters of the single diode PV model and finding optimal sizing of the SAPV system. …”
Get full text
Get full text
Thesis -
5
Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…The described model was resolved by linear programming and evolutionary algorithms in Microsoft Excel (Solver). The results showed full compliance of these two methods. …”
Get full text
Get full text
Get full text
Thesis -
6
-
7
-
8
Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…Experimental results show that the proposed algorithm works better than other two methods in terms of classifier accuracy with result of more than 99 percent successful segmentation of desired color in varying illumination. …”
Get full text
Get full text
Thesis -
9
Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system
Published 2020“…The iterative method is employed for validation of the superiority results of the proposed MS-MOSS algorithm. …”
Get full text
Get full text
Get full text
Article -
10
Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
Get full text
Get full text
Conference or Workshop Item -
11
Battery remaining useful life estimation based on particle swarm optimization-neural network
Published 2024“…Concerning that matter, this study proposed hybrid Particle Swarm Optimization–Neural Network (PSO NN) for estimating battery RUL. …”
Get full text
Get full text
Get full text
Article -
12
-
13
Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
Get full text
Get full text
Thesis -
14
A combined-model for uncertain load and optimal configuration of distributed generation in power distribution system
Published 2017“…The uncertainties in the load are modelled by probability distribution functions (PDF) of load with Hong’s two-point estimation method. …”
Get full text
Get full text
Article -
15
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
Get full text
Get full text
Thesis -
16
Optimum design of a standalone solar photovoltaic system based on novel integration of iterative-PESA-II and AHP-VIKOR methods
Published 2020“…In this study, a novel hybrid sizing approach was developed on the basis of techno-economic objectives to optimally size the SAPV system. The proposed hybrid method consisted of an intuitive method to estimate initial numbers of PV modules and storage battery, an iterative approach to accurately generate a set of wide ranges of optimal configurations, and a Pareto envelope-based selection algorithm (PESA-II) to reduce large configuration by efficacy obtaining a set of Pareto front (PF) solutions. …”
Get full text
Get full text
Get full text
Article -
17
Optimum design of a standalone photovoltaic system based on integration of iterative-PESA-II and AHP-VICKOR methods
Published 2020“…In this study, a novel hybrid sizing approach was developed on the basis of techno-economic objectives to optimally size the SAPV system. The proposed hybrid method consisted of an intuitive method to estimate initial numbers of PV modules and storage battery, an iterative approach to accurately generate a set of wide ranges of optimal configurations, and a Pareto envelope-based selection algorithm (PESA-II) to reduce large configuration by efficacy obtaining a set of Pareto front (PF) solutions. …”
Get full text
Get full text
Get full text
Article -
18
Probabilistic load flow�based optimal placement and sizing of distributed generators
Published 2023Article -
19
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
Get full text
Get full text
Thesis -
20
Sizing and placement of battery-coupled distributed photovoltaic generations
Published 2017“…The optimal planning determines the size and location of BCDPGs and schedules the charging and discharging of the batteries, while minimizing the total energy losses subject to technical constraints. To estimate the output from PV modules, 15-year solar irradiance data is modeled using the beta probability density function. …”
Get full text
Get full text
Article
