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In this paper we use symbolic regression methods for control system synthesis. We compare three methods: network operator method, genetic programming and analytical programming. We developed variational versions of genetic programming and analytical programming to improve the search process efficiency. All the methods perform search over the set of the small variations of the given basic solution...
This document presents the implementation of a Genetic Algorithm (GA) in Matlab software as it is complemented in Guide in order to visualize the GA through a graphic interface, which uses Flexible AC Transmission Systems (FACTS) aimed to enhance the transmission capacity of an Electric Power System, emulating the process of a living organism which afterwards will be evolutionary in order to find...
Electric springs have been used previously in stabilizing mains voltage fluctuations in power grid fed by intermittent renewable energy sources. This paper describes a new three-phase electric spring circuit and its new operation in reducing power imbalance in the three-phase power system of a building. Based on government energy use data for tall buildings, the electric loads are classified as critical...
The problem of multi-objective feedback controller design of nonlinear systems is solved in this paper. The T-S fuzzy model is adopted to describe the nonlinear systems and genetic algorithm is used to identify the T-S fuzzy model. The identified T-S fuzzy model is reduced by applying Higher Order Singular Value Decomposition (HOSVD) method. Based on the reduced T-S fuzzy model, an optimal state feedback...
The main focus of this paper is on system identification of an active magnetic bearing system (AMB) using genetic algorithm (GA) for optimal controller design purpose. In the first step, an analytical model of the system is derived using principle of physics and taking into account both the rigid body and bending body modes of the system. In the next step, as AMB system is inherently open-loop unstable,...
The Internet-of-Things (IoT) aims to connect everything on the Internet. One main advantage of IoT is the task assignment among entities. The task scheduling in IoT is very complex because there exist complex relationship between devices. In this study, we introduce the task scheduling problem with multiple processing sequence relation constraints in IoT system. Several benchmarks are given in this...
A newly introduced Self-adaptive Differential Evolution algorithm via Generalized Opposition-Based Learning (SDE-GOBL) is applied to optimal design of two sewer networks. Every chromosome consists of the information of network layout. Select a feasible design which satisfies the constraints of velocity, slope and proportional water depth to get optimal cost through the algorithm. Two sewer optimization...
Quantum control landscape is generally a physical objective defined as a functional of the control field and plays an important role for the analysis and manipulation of quantum systems. In this paper, we focus on typical learning methods (i.e., gradient decent method, genetic algorithm and deferential evolution) for the landscape control of open quantum systems and explores the characteristics of...
Focusing on the non-stationary characteristic of the fault signal of subway auxiliary inverter, this paper proposes the method that combines ensemble empirical mode decomposition (EEMD) with genetic algorithm to optimize BP neural network (GABP) to diagnose the fault categories of subway auxiliary inverter. Firstly, this paper extracts feature vectors from the original fault signal by EEMD, then establishes...
Tool inventory has a large difference with the traditional static inventory since the tool can be reused by grinding. In this paper, according to the life characteristics of tool, the tool inventory cost model has been built by studying the using process of tool. The model takes all costs which includes the shortage cost in the product life cycle into account under the circumstances of demand uncertainty...
In order to achieve collaborative learning in network learning system, two primary questions must be solved. First is how to choose and quantify the proper features to build user model. Second is how to divide the users into optimal teams to play the best effectiveness of collaborative learning. Based on the collaborative learning theory, its practical research, and the conditions of network learning...
For automating the monitoring works of a Remotely Operated Underwater Vehicle (ROV), we developed a path planning algorithm, which generates a efficient monitoring path for a semi-autonomous ROV. Firstly we categorized five typed sensor information in 2D Euclidean space, and defined the certainty for the sensor information and its space. Moreover, we defined the reliability function for comparing...
Over the years, traffic congestion has grown into one of today's global problems. Intersections are a major cause of this problem. Thus proper management of the intersections, will reduce congestion consequently. In this study, an intelligent Intersection Control System (ICS) is proposed to control traffic flow in intersections. Treating the problem as a Multi-Agent System (MAS), two types of agents...
This paper presents an approach for improving the efficiency of solving linear systems by applying a genetic algorithm (GA) to the GMRES(m) method, which is one of the most powerful solvers of large-scale asymmetric sparse matrices. For each restart process in GMRES(m), the initial vectors are regarded as chromosomes. When the restart process stagnates, the GA process performs a crossover on chromosomes...
Medical imaging research became an important field of investigation that could be very useful for clinical exploration, particularly for serious pathological cases such as cancer. In this proposed clinical aided tool, we were interested at the moment in analysis and exploration for standard segmentation of Positron Emission Tomography (PET) images for the breast cancer characterization. This research...
One of the devices used to determine the attitude of a satellite is the star tracker, whose principle of operation is based on star position measurements on a specific inertial frame, allowing precise attitude determination and control of the satellite. Due to the high sensitivity of star camera, bright objects like Sun, Earth or Moon must be avoided in the sensor's field of view. This characteristic...
The performance of information retrieval is dependent upon how effectively the documents can be ranked according to numeric similarity measure between the query and the document. The cosine and Jaccard are commonly used similarity measures. The authors have presented new similarity measure by combining Cosine and Jaccard similarity measures using fuzzy logic. The experiments are performed on CACM...
Power system operation involves generation, transmission and distribution which involves optimization procedure for ensuring economy, reliability, security and stability. Dynamic economic load dispatch involves an optimization procedure for minimization of fuel cost. Optimization is done by properly scheduling the generator according to the load demand. This paper proposes a comparative analysis of...
Examinations are important tools for assessing student performance. They are commonly used as a metric to determine the quality of the students. However, examination question paper composition is a multi-constraint concurrent optimization problem. Question selection plays a key role in question paper composition system. Question selection is handled in traditional systems by using a specified question...
In this paper, we propose a new method for modeling the electromagnetic radiation of power electronics systems. This method is based on coupling three powerful techniques: the genetic algorithm (GA) used for the optimization problem, the pseudo-Zernike moment invariant (PZMI) descriptors for pattern recognition, and the neural networks for classification of radiating sources. This modeling approach...
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