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001448047 001__ 1448047
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001448047 0247_ $$a10.1007/978-981-16-9416-5$$2doi
001448047 035__ $$aSP(OCoLC)1334886869
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001448047 049__ $$aISEA
001448047 050_4 $$aQ334
001448047 08204 $$a006.3
001448047 1112_ $$aCongress on Intelligent Systems$$n(2nd :$$d2021 :$$cBangalore, India)
001448047 24510 $$aCongress on Intelligent Systems :$$bproceedings of CIS 2021.$$nVolume 1 /$$cMukesh Saraswat, Harish Sharma, K. Balachandran, Joong Hoon Kim, Jagdish Chand Bansal, editors.
001448047 260__ $$aSingapore :$$bSpringer,$$c2022.
001448047 300__ $$a1 online resource (933 pages)
001448047 336__ $$atext$$btxt$$2rdacontent
001448047 337__ $$acomputer$$bc$$2rdamedia
001448047 338__ $$aonline resource$$bcr$$2rdacarrier
001448047 4901_ $$aLecture Notes on Data Engineering and Communications Technologies ;$$vv. 114
001448047 500__ $$a3 Review of Software Architectures
001448047 500__ $$aIncludes author index.
001448047 5058_ $$aPythagorean Fuzzy Information Measure with Application to Multicriteria Decision Making -- 1 Introduction -- 2 Literature Review -- 3 New Pythagorean Fuzzy Information Measure -- 3.1 Properties of O[alpha-Beta] (A) -- 3.2 Monotonicity of Proposed Pythagorean Fuzzy Information Measure -- 3.3 Multicriteria Decision Making Based on New Pythagorean Fuzzy Information Measure -- 4 Conclusion -- References -- Developing an Improved Software Architecture Framework for Smart Manufacturing -- 1 Introduction -- 2 Literature Review -- 2.1 Industry 4.0 -- 2.2 Software Architecture 4.0
001448047 5050_ $$aIntro -- Preface -- Contents -- About the Editors -- The Extraction of Automated Vehicles Traffic Accident Factors and Scenarios Using Real-World Data -- 1 Introduction -- 2 Data Collecting and Preprocessing -- 2.1 Collecting AVs Accident Data -- 2.2 Preprocessing AVs Accident Data -- 3 Learning Method and Result -- 3.1 Random Forest -- 3.2 Extraction of AVs Collision Factor Importance -- 4 AVs Traffic Accident Scenarios -- 4.1 Scenario Combinations Based on Collision Situations -- 4.2 AVs Ahead Situation -- 4.3 AVs Rear Situation -- 4.4 Comparison with HVs Traffic Accidents -- 4.5 Summary
001448047 5058_ $$a5 Conclusion and Future Research -- References -- Leaf Disease Identification in Rice Plants Using CNN Model -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Dataset -- 3.2 Pre-processing -- 3.3 Data Normalization -- 3.4 Create a Model -- 3.5 Training and Validation -- 3.6 Test the Model -- 3.7 Convert the Model to .tflite Format -- 3.8 Develop and Deploy Using Mobile App -- 3.9 Test the Mobile App -- 4 Experimental Results -- 5 Experimental Set-Up -- 6 Discussion -- 7 Conclusions -- References -- Twitter Sentiment Analysis Based on Neural Network Techniques -- 1 Introduction
001448047 5058_ $$a2 Literature Survey -- 2.1 Related Work -- 2.2 Opinion Mining -- 2.3 Twitter -- 2.4 Twitter Sentiment Analysis -- 3 Data Description -- 4 Proposed Methodology -- 4.1 Pre-processing -- 4.2 Feature Extraction -- 4.3 Feature Representation -- 4.4 Handling Memory Issues -- 4.5 Implementation -- 5 Classification Techniques Compared -- 5.1 Naïve Bayes -- 5.2 Decision Tree -- 5.3 Support Vector Machine (SVM) -- 5.4 Multilayer Perceptron (MLP) -- 5.5 Recurrent Neural Network (RNN) -- 5.6 Convolutional Neural Network (CNN) -- 6 Results -- 7 Conclusion -- References
001448047 5058_ $$aEnhanced Stock Market Prediction Using Hybrid LSTM Ensemble -- 1 Introduction -- 2 Literature Survey -- 3 Dataset -- 4 Proposed Methodology -- 4.1 Ensemble -- 4.2 Bagging -- 4.3 Optimizer -- 4.4 Experimental Settings -- 5 Result -- 6 Conclusion -- References -- Classifying Microarray Gene Expression Cancer Data Using Statistical Feature Selection and Machine Learning Methods -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Feature Selection -- 3.3 Classifiers -- 4 Results and Discussion -- 5 Conclusion -- References
001448047 506__ $$aAccess limited to authorized users.
001448047 520__ $$aThis book is a collection of selected papers presented at the Second Congress on Intelligent Systems (CIS 2021), organized by Soft Computing Research Society and CHRIST (Deemed to be University), Bengaluru, India, during September 4 5, 2021. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers topics such as Internet of things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, humancomputer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro-fuzzy systems.
001448047 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 13, 2022).
001448047 650_0 $$aArtificial intelligence$$vCongresses.
001448047 655_0 $$aElectronic books.
001448047 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001448047 7001_ $$aSaraswat, Mukesh.
001448047 7001_ $$aSharma, Harish.
001448047 7001_ $$aBalachandran, K.,$$d1956-
001448047 7001_ $$aKim, Joong Hoon.
001448047 7001_ $$aBansal, Jagdish Chand.
001448047 77608 $$iPrint version:$$aSaraswat, Mukesh.$$tCongress on Intelligent Systems.$$dSingapore : Springer, ©2022$$z9789811694158
001448047 830_0 $$aLecture notes on data engineering and communications technologies ;$$vv. 114.
001448047 852__ $$bebk
001448047 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-9416-5$$zOnline Access$$91397441.1
001448047 909CO $$ooai:library.usi.edu:1448047$$pGLOBAL_SET
001448047 980__ $$aBIB
001448047 980__ $$aEBOOK
001448047 982__ $$aEbook
001448047 983__ $$aOnline
001448047 994__ $$a92$$bISE