The connection weights between processing elements contain the knowledge stored in the artificial neural network model. Usually‚ the processing elements are classified as input units‚ output units‚ or hidden units. The basic structure of an ANN usually consists of three layers: (1) the input layer‚ where the data are introduced to the network; (2) the hidden layer(s)‚ where data are processed; and (3) the output layer‚ where the results of given input are produced. The
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It is a well-known fact that Sri Lankans life style has been drastically changed recently. Health department’s researches corroborate the above. As result of the change of life style people have unknowingly neglected the value of balance‚ nutritious diet and they have forgotten the importance of the schedule of daily exercises that enables to keep a healthy body. I do say‚ people both rich and poor are unaware of the values of three main meals. Particularly‚ rich people tend to consume instant foods
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technologies tools is the Artificial Neural Networks which work much like the human brain and have the ability to learn from training data and store knowledge in the network. In the learning phase‚ it maps relation between inputs and the corresponding expected outputs. Neural networks are frequently used as diagnostics‚ and therefore it is important to have good generalization ability‚ that is‚ good performance in predicting results in response to unseen data. Neural networks have found the majority of
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Take Artificial Neutral Network for example. An Artificial Neural Network (ANN) is a mathematical model or computational model. Though ANN is already a classical technique frequently applied in fields like computer vision‚ natural language processing‚ optimized computing‚ pattern recognition‚ automatic control‚ and development of neural computer all of which are branches of computer science‚ it is inspired by the structure and functional aspects of biological neural networks. As a matter of fact‚ ANN
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Real Time Road Sign Recognition System Using Artificial Neural Networks For Bengali Textual Information Box An Automated Road Sign Recognition system using Artificial Neural Network for the Textual Information box inscribing in Bengali is presented on the paper. Signs are visual languages that represent some special circumstantial information of environment. Road signs‚ being among the most important around us primarily for safety reasons‚ are designed‚ and manufactured and installed according
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4. ANFIS: On the basis of Takagi-Sugeno Fuzzy interference system the ANFIS or the Adaptive Network Based Fuzzy Inference is one kind of AI or Artificial Intelligence. In the 1990s this technique was developed as it combines the two forms the Fuzzy Logic Principles and as well as the Neural Networks. It can gather both the framework. The interference system correlates to the set of the IF-THEN functions which are non linear to be approximated using this rules it has a capability to learn. Thus it
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Abstract- The paper is aimed to design and develop Graphical User Interface (GUI) named GyroDataAnalyser to enhance the statistical and stochastic analysis of the tri-axial gyroscopes. This GUI identifies the dominant stochastic noises associated with the gyroscope data using Allan Variance technique. The unique feature of this GUI is to provide the estimates of the stochastic noise coefficients without much human intervention. GUI is designed using MATLAB GUIDE environment to provide simple interface
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Results Properties of social networks Mean network size was 80.67 (SD = 39.84‚ Mdn = 75)‚ with a range of 10–279 (Figure 1). The shape of the distribution is similar to that found in other studies of social networks (Bernard et al.‚ 1990; Hill & Dunbar‚ 2003). The size of the kin and friend networks is given in Table 1. Multilevel models The results of the two models are presented Table 2. The intraclass correlations (ICCx) of the models were 0.18 for Model 1 and 0.24 for Model 2
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Neural Network Predictions of Stock Price Fluctuations By Wojciech Gryc (wojciech@gmail.com) Table of Contents Abstract...................................................................................................................................................... 3 Introduction................................................................................................................................................3 Part 1: The Stock Market Stock Market Psychology..............
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Kenya Methodist University DLM instructional material KENYA METHODIST UNIVERSITY DLM BOOKLET FAULTY : COMPUTING AND INFORMATICS DEPARTMENT : COMPUTER SCIENCE COURSE CODE COURSE NAME LECTURER CONTACT : CISY422/BBIT333 : ARTIFICIAL INTELLIGENCE : ROBERT MUTUA MURUNGI : 0710 480 450‚ r_mutua@yahoo.com 1st edition ©2012 Artificial Intelligence by Robert Mutua Murungi – I.T Lecturer 1 Kenya Methodist University DLM instructional material KENYA METHODIST UNIVERSITY P.O.
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