Search results for "optimization algorithm"
showing 10 items of 51 documents
A novel identification method for generalized T-S fuzzy systems
2012
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/893807 In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulation results show the effectiveness of the proposed algorithm
Enhanced flexible algorithm for the optimization of slot filling factors in electrical machines †
2020
The continuous development in the field of industrial automation and electric mobility has led to the need for more efficient electrical machines with a high power density. The improvement of electrical machines’ slot filling factors is one of the measures to satisfy these requirements. In recent years, this topic has aroused greater interest in the industrial sector, since the evolution of the winding technological manufacturing processes allows an economically sustainable realization of ordered winding arrangements, rather than random ones. Moreover, the manufacture of electrical machines’ windings must be preceded by an accurate design phase in which it is possible to evaluate the maximu…
A Study on scale factor in distributed differential evolution.
2011
This paper proposes the employment of multiple scale factor values within distributed differential evolution structures. Four different scale factor schemes are proposed, tested, compared and analyzed. Two schemes simply employ multiple scale factor values and two also include an update logic during the evolution. The four schemes have been integrated for comparison within three recently proposed distributed differential evolution structures and tested on several various test problems. Numerical results show that, on average, the employment of multiple scale factors is beneficial since in most cases it leads to significant improvements in performance with respect to standard distributed alg…
Surrogate-Assisted Evolutionary Optimization of Large Problems
2019
This chapter presents some recent advances in surrogate-assisted evolutionary optimization of large problems. By large problems, we mean either the number of decision variables is large, or the number of objectives is large, or both. These problems pose challenges to evolutionary algorithms themselves, constructing surrogates and surrogate management. To address these challenges, we proposed two algorithms, one called kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) for many-objective optimization, and the other called cooperative swarm optimization algorithm (SA-COSO) for high-dimensional single-objective optimization. Empirical studies demonstrate that K-RVEA works…
A predictive function optimization algorithm for multi-spectral skin lesion assessment
2015
The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique used in the assessment of skin lesions. Unfortunately, this method is computationally expensive due to its function inverting process. In the work of this paper, we design a Predictive Function Optimization Algorithm in order to improve the efficiency of KMGA by speeding up its convergence rate. Using this approach, a High-Convergence-Rate KMGA (HCR-KMGA) is implemented onto multi-core processors and FPGA devices respectively. Furthermore, the implementations are optimized using parallel computing techniques. Intensive experiments demonstrate that HCR-KMGA can effectively accelerate KMGA method, while improv…
An Application of Ant Colony Optimization to Decision Making on Affective Virtual Entities
2007
Learning is a never ending activity for humans; it takes place everywhere and even when we do not realize. However, current learning environments make students deal with lectures, mostly associated with low control of the situation and implicit motivation. In contrast, previous researches have shown that sports, games or hobbies are activities that make people reach optimal experiences where self-motivation, control of the situation, high level of concentration and enjoyment are present. Some current efforts to design next generation of learning environments make use of ubiquitous systems to encourage students to perform learning activities everywhere and at anytime. However, those approach…
Registration and fusion of segmented left atrium CT images with CARTO electrical maps for the ablative treatment of atrial fibrillation
2005
This study aims to extract the interior surface of the left atrium (LA) and pulmonary veins (PVs) from threedimensional tomographic data and to integrate it with LA CARTO electrical maps. The separation of LA and PVs from other overlapping structures of the heart was performed processing 3D CT data by marker-controlled watershed segmentation and surface extraction. CARTO maps were then registered on the L A internal surface by a stochastic optimization algorithm based on simulated annealing. The residual registration error resulted inferior to 3 mm. The integration between electrophysiological and high resolved anatomic information of LA results feasible and may constitute a significant sup…
An ant colony optimization-based fuzzy predictive control approach for nonlinear processes
2015
In this paper, a new approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the ant colony optimization (ACO) is proposed. On-line adaptive fuzzy identification is introduced to identify the system parameters. These parameters are used to calculate the objective function based on a predictive approach and structure of RST control. Then the optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to determine optimal controller parameters of RST control. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, where the proposed approach provides better performances compared with p…
Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms
2016
We study how different types of preference information coming from a human decision maker can be utilized in an interactive multiobjective evolutionary optimization algorithm (MOEA). The idea is to convert different types of preference information into a unified format which can then be utilized in an interactive MOEA to guide the search towards the most preferred solution(s). The format chosen here is a set of reference vectors which is used within the interactive version of the reference vector guided evolutionary algorithm (RVEA). The proposed interactive RVEA is then applied to the multiple-disk clutch brake design problem with five objectives to demonstrate the potential of the idea in…
Determination of water speciation in hydrous haplogranitic glasses with partial Raman spectra
2020
Abstract We use a mathematical approach to decompose the Raman water band at 3000 cm−1 to 3750 cm−1 into two partial Raman spectra corresponding to the individual Raman activity of the two water species, i.e., molecular water (H2Om) and OH-groups, present in hydrous rhyolitic glasses. The approach is based on a least-squares optimization algorithm and the assumption that the water band can be expressed as a linear combination of two partial Raman spectra. Our model makes no assumptions regarding the shape of the partial Raman spectra. The model input consists of about 700 Raman spectra from hydrous haplogranitic (HPG8) compositions with total water contents from 0.6 to 3.1 wt% and with know…