Pacific School of Engineering Dept: CSE Semester: 7th Subject: Soft Computing Assignment-1 Q. 1. Explain the working of Artificial Neuron and compare it with biological neuron Q. 2. Discuss Back Propagation Algorithm in detail with proper illustration. Q. 3. Compare: I. Supervised Vs. Unsupervised Learning II. Hard Computing Vs. Soft Computing III. Single Layer Vs. Multilayer Perceptron Q. 4. Write a short note on: I. Radial Basis Function II. LVQ Q. 5. Discuss various operations of fuzzy
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------------------------------------------------- ------------------------------------------------- ------------------------------------------------- ------------------------------------------------- KEYWORDS optimization‚ electrical discharge machining‚ soft computing‚ artificial neural network‚ fuzzy logic‚ evolutionary algorithms‚ -------------------------------------------------
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SOFT COMPUTING social sciences behavioral sciences the humanities economics law medicine include quantitative Human sciences methods are methods are often used separately qualitative that means numerical data precise objects conventional logic complicated mathematics computer models that means non-numerical data imprecise objects approximate reasoning interpretation manual work 2 Traditional Approaches to Computerized Modeling • Mathematical
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Analysis and Neural Networks Group Department of Computing University of Exeter UK (s.singh@exeter.ac.uk) ABSTRACT Spiral structures are one of the most difficult patterns to classify. Spiral time series data has a helical movement with time that is both difficult to predict as well as classify. This paper focusses on how structural information about spirals can be useful in providing critical information to a neural network for their recognition. Results are presented on neural network solutions
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Comparative Evaluation Of Symbolic Learning Methods and Neural Learning Methods Shravya Reddy Konda Department of Computer Science University of Maryland‚ College Park Email: shravyak@cs.umd.edu Abstract In this paper‚ performance of symbolic learning algorithms and neural learning algorithms on different kinds of datasets has been evaluated. Experimental results on the datasets indicate that in the absence of noise‚ the performances of symbolic and neural learning methods were comparable in most of the
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INTRODUCTION Artificial Intelligence approaches can be
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PAPER PRESENTATION ON “Artificial Intelligence” AUTHORS Shahabaz.S (97907647063) Prabhakaran.S (9629296869) shahabazboss2@gmail.com praba.enamour@gmail.com CONTENT 1. Abstract 2. Introduction 3. What is AI 4. Abstract: This paper is about Artificial intelligence which is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion. This generally
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Image Retrieval Based on Color and Texture Feature Using Artificial Neural Network Syed Sajjad Hussain#1‚ Manzoor Hashmani#2‚ Muhammad Moin uddin#3 # Faculty of Engineering‚ Sciences and Technology‚ IQRA University‚ Karachi 1 engr.sajjadrizvi@yahoo.com‚ 2mhashmani@yahoo.com‚ 3mmoin73@yahoo.com Abstract. Content-based image retrieval CBIR is a technique that helps in searching a user desired information from a huge set of image files and interpret user intentions for the desired information
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Data Plans for iPhone 5 starting November 2 » Airtel’s state of the art Network Experience Centre goes LIVE Business Divisions Mobile Services bharti airtel offers GSM mobile services in all the 22-telecom circles of India and is the largest mobile service provider in the country‚ based on the number of customers. Airtel Telemedia Services The group offers high-speed broadband with the best in class network. With fixed line services in 87 cities‚ we help you stay in touch with your
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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
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