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Soft Computing for Problem Solving 2019

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Cover of 'Soft Computing for Problem Solving 2019'

Table of Contents

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    Book Overview
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    Chapter 1 Exponential Adaptive Strategy in Spider Monkey Optimization Algorithm
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    Chapter 2 Development of Fuzzy Knowledge-Based System for Water Quality Assessment in River Ganga
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    Chapter 3 A Hybrid Framework for Fire Outbreak Detection Based on Interval Type-2 Fuzzy Logic and Flower Pollination Algorithm
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    Chapter 4 Using Convolutional Neural Networks to Predict Colon Cancer Patients Survival
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    Chapter 5 An Array P System Based on a Variant of Pure 2D Context-Free Grammars
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    Chapter 6 Predictions of Weekly Slope Movements Using Moving-Average and Neural Network Methods: A Case Study in Chamoli, India
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    Chapter 7 Two-Stage History Matching for Hydrology Models via Machine Learning
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    Chapter 8 An Intelligent System for Diagnosis of Diabetic Retinopathy
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    Chapter 9 Markov Chain Models for the Near Real-Time Forecasting of Australian Football League Match Outcomes
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    Chapter 10 Genetically Optimized Deep Neural Learning for Breast Cancer Prediction
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    Chapter 11 Optimization of Lycopene Extraction from Tomato Processing Waste Skin Using Harmony Search Algorithm
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    Chapter 12 Meme-Based Computational Optimization Framework
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    Chapter 13 Heterogeneous Multi-robot Mission Planning for Coordinated Tasks Execution
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    Chapter 14 Development of Cost-Effective Endurance Test Rig with Integrated Algorithm for Safety
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    Chapter 15 Development of an Algorithm for the EMG Control of Prosthetic Hand
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    Chapter 16 Improving Data Quality in the Cargo Industry with Modern Recurrent Neural Network Architecture
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    Chapter 17 Temporal Convolution in Spiking Neural Networks: A Bio-mimetic Paradigm
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Title
Soft Computing for Problem Solving 2019
Published by
Springer Singapore, May 2020
DOI 10.1007/978-981-15-3287-0
ISBNs
978-9-81-153286-3, 978-9-81-153287-0
Editors

Nagar, Atulya K., Deep, Kusum, Bansal, Jagdish Chand, Das, Kedar Nath

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