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This paper presents a method to estimate a transformer health condition based on diagnostic tests. A feed forward artificial neural network (FFANN) is used to find the health index of the transformer. The health index is used to find the health condition of the transformer. The training of the FFANN is done using real measurements of 59 working transformers. The testing of the trained neural network...
Responses of chemoresistive gas sensors suffer from the influences of the variations of the ambient humidity and temperature. An appropriate countermeasure is required if any qualitative and quantitative analysis is going to be implemented based on these responses. Here, a novel compensation method based on the fuzzy modeling of the sensor behavior is presented. Gas sensor is treated as a nonlinear...
In this paper, a new method based on the Artificial Bee Colony (ABC) for determining the Schottky barrier height (Φb), ideality factor (n) and series resistance (RS) of a Schottky barrier diode (SBD) model using forward current-voltage (I-V) characteristics, is described. For this SBD model, the Ni/n-GaAs/In Schottky barrier diode was produced in a laboratory and the I-V characteristics of the SBD...
In this paper, a new method is proposed to design a sliding mode controller with variable boundary layer for a nonlinear system. In this method, model predictive control (MPC) is used to predict the future boundary layer thickness. In order to predict the behavior of the nonlinear system, a neural network model is used as an internal model. The simulation results show the supremacy of this method...
The lead time estimation is significant activity in each corporation that concerns with the breakdown of machines and maintenance. An integrated algorithm for forecasting weekly lead time based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed in this study. First, an ANFIS model is illustrated for the lead time forecasting simultaneously. The lowest Mean Absolute Percentage Error (MAPE)...
A design scheme of remote model predictive control system is presented in this paper. Combined with the asynchronous messaging framework Errai, a network application system for remote model predictive control, which is based on GWT architecture, is developed and implemented by using RIA technique. The application field of MPC product is extended and the application function is expanded effectively...
An adaptive neural control scheme based on a new observer applied to quadrotors Helicopter is proposed in this paper. This technique is realized by using two parallel feedforward Artificial Neural Networks (ANN) for each subsystem of the quadrotor. The first one estimates on line the equivalent control term and the second ANN generates observer's corrective term. The main purpose in our work is to...
In this paper, a novel algorithm for classification called “NSSAC” is proposed, which is based on negative selection method in the human immune system. Artificial immune based classifiers have two important challenges: (1) the recognition distance threshold which choosing an appropriate recognition distance threshold is a difficult task because it necessitates the understanding of the data set in...
This paper discusses signature verification and recognition using a new approach that depends on a neural network which enables the user to recognize whether a signature is original or a fraud. The user introduces into the computer the scanned images, modifies their quality by image enhancement and noise reduction techniques, to be followed by feature extraction and neural network training, and finally...
Finding frequent patterns in data mining plays a significant role for finding the relational patterns. In this study an extendable and improved itemset generation approach has been constructed and developed for mining the relationships of the symptoms and disorders in the medical databases. The algorithm of the developed software finds the frequent illnesses and generates association rules using Apriori...
The main purpose of forecasting in financial markets is to estimate future trends and to reduce risks of decision making. This research suggests an ANFIS model to improve prediction accuracy in stock price forecasting. For doing so, we applied fuzzy subtractive clustering for structure identification of our ANFIS model. We implemented the proposed model for predicting Tehran Stock Exchange Price Index...
Traveling Salesman Problem is an important optimization issue of many fields such as transportation, logistics and semiconductor industries and it is about finding a Hamiltonian path with minimum cost. To solve this problem, many researchers have proposed different approaches including metaheuristic methods. Artificial Bee Colony algorithm is a well known swarm based optimization technique. In this...
In the field of cluster analysis, most clustering algorithms consider the contribution of each attribute for classification uniformly. In fact, different attributes (or different features) should be of different contribution for clustering result. In order to consider the different roles of each attribute, this paper proposes a new approach for clustering algorithms based on weights, in which decision...
In this paper, An optimal fuzzy system (OFS), instead of crisp threshold values, have been used for optimal reliability-based multi-objective Pareto design of robust state feedback controllers for a two-mass-spring system having parameters with probabilistic uncertainties. The objective functions that have been considered are, namely, the probabilities of failure of settling time (PTs), of control...
In this work we propose Multi-Objective Artificial Bee Colony for solving multi objectives problems. This algorithm is applied on a base case cogeneration optimization problem with two-objective functions named the modified CGAM problem. The first objective function is exergetic efficiency that should be maximized. The second objective function is the total cost rate that should be minimized. then...
One of the topics during the last 30 years much research has been allocated to cost estimation for software projects. Important issues in the field of software engineering capabilities estimate size and effort required for development of software projects. Cost estimates must be made at the beginning of the project, and principally at the beginning of projects through cost and set new work requirements...
In this paper a method for detecting semantic concepts in soccer video based on Bayesian Belief Network (BBN) classifier is proposed. In most broadcast soccer videos, replays succeed excitement clips. Replays often stand between two successive logos. Here neural network learning is used to detect logos. Events such as close-ups of players, close-ups of referees, staple line in corner point, spectators...
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