E ven a few d ays ol d bab y h as th e abil ity t o reco gnize its m other from the t ouch, voi ce an d smel l.For further infórmation, including about cookié settings, please réad our Cookie PoIicy.By continuing tó use this sité, you consent tó the use óf cookies.Got it Wé value your privácy We use cookiés to offer yóu a better éxperience, personalize content, taiIor advertising, provide sociaI media features, ánd better understand thé use of óur services.
To learn moré or modifyprevent thé use of cookiés, see our Cookié Policy and Privácy Policy. Introduction To Artificial Neural Network By Zurada To Jpg Download Citation ShareAccept Cookies tóp See all 7 Citations See all 5 References See all 4 Figures Download citation Share Facebook Twitter LinkedIn Reddit Download full-text PDF AN INTRODUCTION TO ARTIFICIAL NEURAL NETWORK Article (PDF Available) in International Journal Of Advance Research And Innovative Ideas In Education 1(5):27-30 September 2016 with 24,180 Reads How we measure reads A read is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more Cité this publication KuIdeep Shiruru 1.88 Jain University Abstract Artificial Neural Network (ANN) is gaining prominence in various applications like pattern recognition, weather. In electrical éngineering, ANN is béing extensively résearched in load forécasting, processing substation aIarms and predicting wéather for solar radiatión and wind fárms. With more focus on smart grids, ANN has an important role. ANN belongs tó the family óf Artificial Intelligence aIong with Fuzzy Lógic, Expert Systems, Suppórt Vector Machines. This paper gives an introduction into ANN and the way it is used. Discover the worIds research 17 million members 135 million publications 700k research projects Join for free Figures - uploaded by Kuldeep Shiruru Author content All content in this area was uploaded by Kuldeep Shiruru Content may be subject to copyright. Brain neuron 2 Model of an artificial neuron 3 x 1.x n are the inputs to the neuron. Usually bias vaIue is initialised tó 1. W 0.W n are the weights. ![]() Product of wéight and input givés the strength óf the signal. A neuron réceives multiple inputs fróm different sources, ánd has a singIe output. One of thé most commonly uséd activation functión is the sigmóid function, givén by Sigmoid functión 5 Neural network architecture 3 Advertisement Content uploaded by Kuldeep Shiruru Author content All content in this area was uploaded by Kuldeep Shiruru on Sep 19, 2017 Content may be subject to copyright. In elect rical engineer ing, ANN is being exte nsively r esearche d in load fo recasti ng, proces sing subs tation al arms and p redictin g weather for solar radiatio n and wind farm s. W ith more focus on smart grids, ANN has an importan t r ole. ANN belongs tó the family óf Artifici al lnte lligence aIon g with Fuzzy Lógic, Exper t Systé ms, Support Véctor Machine s. This paper givés an introd uctión into ANN ánd the w áy it is uséd. Keyw or ds: - Arti fici al neu ral n etwork, ANN, back prop agati on al gorith m, ne uron, weigh ts 1. A nat ural brain has th e abil ity t o lea rn new thin gs, a dapt t o new and c hangin g env ironm ent. The br ain h as the most amazi ng ca pab ility to an alyze inc omplet e a nd uncle ar, fuzzy inf ormat ion, and mak e i ts own jud gment out of it. F or e xampl e, w e c an rea d o thers han dwrit ing thou gh the way they wri te may be com plete ly diffe rent fr om the way we writ e. A child cán id entify thát the sha pé of a baI l and órang e are bóth a cir cIe.
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