Kooperativer Bibliotheksverbund

UID:

Format: X, 358 p. 209 illus., 129 illus. in color. , online resource.

Edition: 1st ed. 2022.

ISBN: 9783031117138

Series Statement: Artificial Intelligence-Enhanced Software and Systems Engineering, 1

Content: This book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques, along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains, are discussed in this book and help global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. Novel ways are also discovered to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms leads beginners to apply current approaches to optimization problems. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract researchers and practitioners to apply hybrid metaheuristics in real scenarios.

Note: Performance analysis of Heuristic optimization algorithms for Transportation problem -- Source Code Features Based Branch Coverage Prediction using Ensemble Technique -- Implicit Methods of Multi-Factor Authentication -- Comparative Analysis of different Classifiers Using Machine Learning Algorithm for Diabetes Mellitus -- Survey on Machine Learning Techniques for Software Reliability Accuracy Prediction -- Classification of Pest in Tomato Plants using CNN -- Deep Neural Network Approach For Identifying Good Answers in Community Platforms -- Time Series Analysis of SAR-Cov-2 virus in India using Facebook's Prophet -- Model-Based Smoke Testing Approach of Service Oriented Architecture (SOA) -- Role of Hybrid Evolutionary Approaches for Feature Selection in Classification: A Review -- Evaluation of Deep Learning Models for Detecting Breast Cancer using Mammograms -- Evaluation of Crop Yield Prediction using arsenal and Ensemble Machine learning algorithms -- Notification Based Multichannel MAC (NM-MAC) Protocol for Wireless Body Area Network -- A multi Brain Tumor Classification using a Deep Reinforcement Learning Model -- A Brief Analysis on Security in Healthcare Data using Blockchain -- A Review on Test Case Selection, Prioritization and Minimization in Regression Testing -- Artificial Intelligence Advancement in Pandemic Era -- Predictive technique for Identification of Diabetes using Machine Learning -- Prognosis of Prostate Cancer Using Machine Learning -- Sign language Detection Using Tensorflow Object Detection -- Automated Test Case Prioritization using Machine Learning -- A New Approach To Solve Linear Fuzzy Stochastic Differential Equation -- An Improved Software Reliability Prediction Model by Using Feature Selection and Extreme Learning Machine -- Signal Processing Approaches for Encoded Protein Sequences in Gynaecological Cancer Hotspot Prediction: A Review -- DepNet: Deep Neural Network based model for Estimating the Crowd Count -- Dynamic Stability enhancement of Power system by Sailfish Algorithm tuned fractional SSSC control action -- Application of Machine Learning Model Based Techniques for Prediction of Heart Diseases -- Software Effort and Duration Estimation using SVM and Logistic Regression -- A framework for ranking cloud services based on an integrated BWM-Entropy-TOPSIS Method -- An Efficient and Delay-Aware Path Construction Approach Using Mobile Sink in Wireless Sensor Network -- Application of Different Control Techniques of multi-area Power Systems -- Analysis of An Ensemble Model For Network Intrusion Detection -- D2D Resource Allocation for Joint Power Control in Heterogeneous Cellular Networks -- Prediction of Covid-19 Cases in Kerala based on meteorological parameters using BiLSTM Technique.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031117121

Additional Edition: Printed edition: ISBN 9783031117145

Additional Edition: Printed edition: ISBN 9783031117695

Language: English

DOI: 10.1007/978-3-031-11713-8

URL: https://doi.org/10.1007/978-3-031-11713-8

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: 1 online resource (368 pages)

ISBN: 3-031-11713-1

Series Statement: Artificial Intelligence-Enhanced Software and Systems Engineering ; v.1

Note: Intro -- Preface -- Contents -- Performance Analysis of Heuristic Optimization Algorithms for Transportation Problem -- 1 Introduction -- 2 Mathematical Model of TP -- 3 Optimization Algorithms -- 3.1 PSO -- 3.2 APSO -- 3.3 NQPSO -- 4 Steps of Optimization -- 5 Performance Evaluation of the Algorithms -- 5.1 Convergence -- 5.2 Optimization Value -- 5.3 Accuracy -- 6 Conclusion -- References -- Source Code Features Based Branch Coverage Prediction Using Ensemble Technique -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 4 Implementation and Result Analysis -- 4.1 Result Analysis -- 4.2 Feature Analysis -- 5 Comparison with Related Work -- 6 Conclusions and Future Work -- References -- Implicit Methods of Multi-factor Authentication -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Implicit Methods of Multifactor Authentication -- 4.1 Mouse Events as Passcode -- 4.2 Image as Passcode -- 4.3 Patterned OTP -- 5 Implementation -- 5.1 Mouse Events as Passcode -- 5.2 Image as Passcode -- 5.3 Patterned Based OTP -- 6 Experimental Results -- 6.1 Mouse Events as Passcode -- 6.2 Image as Passcode -- 6.3 Pattern Based OTP -- 7 Analysis -- 7.1 Usability -- 7.2 Security and Privacy -- 8 Conclusion -- References -- Comparative Analysis of Different Classifiers Using Machine Learning Algorithm for Diabetes Mellitus -- 1 Introduction -- 2 Related Work -- 2.1 Control Mechanism Process for Diabetes Mellitus -- 2.2 Focus on Digital System -- 2.3 Medication -- 2.4 Diabetes Services -- 2.5 Psychological Issues and Tensity -- 3 Methodology -- 3.1 Data Gathering -- 3.2 Data Prediction -- 3.3 Implementation of Classifier for Evaluation of Accuracy -- 4 Proposed Architecture -- 5 Logistic Regression -- 6 K-Nearest Neighbors Algorithms (K-NN) -- 7 CART (Classification and Regression Tree) -- 8 Conclusion -- References. , Survey on Machine Learning Techniques for Software Reliability Accuracy Prediction -- 1 Introduction -- 2 Research Methodology and Contribution -- 3 Reliability Measurement Methods and Process -- 4 Related Work -- 5 Motivations and Objectives -- 5.1 Motivation -- 5.2 Objective -- 6 Methodology -- 6.1 Axes of Quality Evaluation -- 6.2 Technical Catalogue -- 7 Evaluation Criteria -- 8 Experiments and Results -- 8.1 Defect Prediction -- 9 Conclusion -- References -- Classification of Pest in Tomato Plants Using CNN -- 1 Introduction -- 2 Materials and Methods -- 2.1 Sample Collection -- 2.2 Hardware Setup -- 2.3 Software Setup -- 2.4 Image Processing -- 2.5 Design and Setup of Data and CNN Architecture -- 3 Results and Discussion -- 3.1 Comparison with Existing Works -- 3.2 Limitations -- 4 Conclusions -- References -- Deep Neural Network Approach for Identifying Good Answers in Community Platforms -- 1 Introduction -- 2 Ranking and Tagging of Quality Answers in CQA -- 2.1 Tagging Answers in CQA Using Ensemble Deep Learning Model -- 3 Results and Discussion -- 4 Conclusion and Future Direction -- References -- Time Series Analysis of SAR-Cov-2 Virus in India Using Facebook's Prophet -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection -- 2.2 Testing -- 2.3 Data Visualization -- 2.4 Comparison -- 2.5 Facebook's Prophet -- 3 Conclusion and Future Work -- References -- Model-Based Smoke Testing Approach of Service Oriented Architecture (SOA) -- 1 Introduction -- 2 Related Works on ERP -- 3 Overview of SOA Testing and Smoke Testing -- 3.1 The Importance of SOA -- 3.2 Challenges in SOA Testing -- 3.3 Smoke Testing -- 4 Case Study: Enterprise Resource Planning (ERP) -- 5 Conclusion -- References -- Role of Hybrid Evolutionary Approaches for Feature Selection in Classification: A Review -- 1 Introduction -- 2 Background -- 2.1 Searching Techniques. , 2.2 Criteria for Evaluation -- 2.3 Number of Objectives -- 3 Systematic Literature Review -- 3.1 Thawkar et al. (2021) [30] -- 3.2 Hussain et al. (2021) [32] -- 3.3 Wajih et al. (2021) [33] -- 3.4 Bindu et al. (2020) [3] -- 3.5 Bhattacharyya et al. (2020) [6] -- 3.6 Alweshah et al. (2020) [7] -- 3.7 Meera et al. (2020) [8] -- 3.8 Neggaz et al. (2020) [9] -- 3.9 Hans et al. (2020) [29] -- 3.10 Khamees et al. (2020) [37] -- 4 Analysis -- 5 Conclusion -- References -- Evaluation of Deep Learning Models for Detecting Breast Cancer Using Mammograms -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methods -- 4 Simulation Environment -- 5 Experimental Results -- 6 Conclusion -- References -- Evaluation of Crop Yield Prediction Using Arsenal and Ensemble Machine Learning Algorithms -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Basic Terminologies -- 4 Module Description -- 4.1 Module 1 - Data Acquisition -- 4.2 Module 2 - Exploratory Data Analysis -- 4.3 Module 3 - Preprocessing -- 4.4 Module 4 - Model Evaluation -- 5 GUI Application -- 5.1 Application Functionality -- 6 Results and Discussion -- 7 Conclusion and Future Scope -- References -- Notification Based Multichannel MAC (NM-MAC) Protocol for Wireless Body Area Network -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 3.1 Data Type Organisation -- 3.2 Notification Based Multichannel MAC Protocol -- 4 Simulation Results -- 5 Conclusion and Future Scope -- References -- A Multi Brain Tumor Classification Using a Deep Reinforcement Learning Model -- 1 Introduction -- 1.1 Brain Tumor -- 1.2 Glioma Tumor -- 1.3 Meningioma Tumor -- 1.4 Pituitary Tumors -- 1.5 Dataset -- 2 Related Work -- 3 Proposed Model -- 3.1 Convolution Neural Networks -- 3.2 Reinforcement Learning -- 3.3 Deep Q-Learning -- 3.4 Confusion Matrix -- 4 Experimental Results -- 5 Conclusion -- References. , A Brief Analysis on Security in Healthcare Data Using Blockchain -- 1 Introduction -- 2 Overview of Blockchain -- 2.1 Properties of Blockchain -- 2.2 Types of Blockchain -- 2.3 Blockchain in Healthcare -- 3 Related Work -- 4 Discussion -- 5 Conclusion and Future Scope -- References -- A Review on Test Case Selection, Prioritization and Minimization in Regression Testing -- 1 Introduction -- 2 Basic Concepts -- 2.1 Regression Testing -- 2.2 Effectiveness of Prioritized Test -- 3 Related Work -- 4 Conclusion and Future Scope -- References -- Artificial Intelligence Advancement in Pandemic Era -- 1 Introduction -- 2 Artificial Intelligence -- 2.1 Artificial Intelligence Role in the Treatment of COVID-19 -- 2.2 Artificial Intelligence as a Catalyst for the Exchange of Information -- 2.3 Role of Artificial Intelligence as an Observer and Predictor in the Pandemic Evolution -- 2.4 Healthcare Personnel Assistance with Artificial Intelligence -- 3 AI and ML to Combat Covid-19 -- 3.1 Developing Novel COVID-19 Antibody Sequences for the use in Experimental Testing Using the Machine Learning -- 3.2 CT Scan Checks with AI for COVID-19 -- 3.3 AI as an Aid in the Transmission of COVID-19 -- 4 Conclusion -- References -- Predictive Technique for Identification of Diabetes Using Machine Learning -- 1 Introduction -- 2 Literature Review -- 3 Prediction of Healthcare Data Using AI and ML -- 4 Results -- 5 Conclusion -- References -- Prognosis of Prostate Cancer Using Machine Learning -- 1 Introduction -- 1.1 Correlation Between Machine Learning and Healthcare Databases -- 2 Literature Review -- 3 Outline of Research -- 4 Result -- 4.1 The Yearly Incidence Rate and the Mortality Rate of Prostate Cancer. -- 4.2 The Age-Based Incidence Rate and Mortality Rate of Prostate Cancer -- 5 Conclusion -- References -- Sign Language Detection Using Tensorflow Object Detection. , 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Labelling Images -- 3.3 TF Record Generation -- 3.4 Creating Model Configuration File -- 3.5 Training Model -- 4 Result and Discussion -- 5 Conclusion -- References -- Automated Test Case Prioritization Using Machine Learning -- 1 Introduction -- 2 System Overview -- 3 Literature Survey and Problem Definition -- 4 Proposed Solution -- 5 Result and Future Scope -- 6 Conclusion -- References -- A New Approach to Solve Linear Fuzzy Stochastic Differential Equation -- 1 Introduction -- 2 Basic Preliminaries -- 2.1 Stochastic Differential Equation [7] -- 2.2 Linear Stochastic Differential Equation [7] -- 2.3 Brownian Motion (BM) [7] -- 2.4 Fuzzy Brownian Motion (FBM) [9] -- 2.5 Fuzzy Ito Formula (FIF) [9] -- 2.6 Stochastic Process (SP) [7] -- 2.7 Fuzzy Stochastic Process (FSP) [9] -- 2.8 Adapted Process [7] -- 2.9 Fuzzy Ito Product [9] -- 3 Linear Fuzzy Stochastic Differential Equation (LFSDE) -- 4 Conclusion -- References -- An Improved Software Reliability Prediction Model by Using Feature Selection and Extreme Learning Machine -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Collection of Data -- 3.2 Preparation of Data -- 3.3 Feature Selection -- 3.4 Training the ELM Classifier -- 3.5 Testing and Calculation of Accuracy -- 4 Results and Analysis -- 5 Conclusion -- References -- Signal Processing Approaches for Encoded Protein Sequences in Gynecological Cancer Hotspot Prediction: A Review -- 1 Introduction -- 2 Materials and Methods -- 2.1 Hotspot Prediction in Proteins -- 2.2 Hotspot Prediction in Cancer Cells -- 3 Conclusions -- References -- DepNet: Deep Neural Network Based Model for Estimating the Crowd Count -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Density-Estimation Based Approach -- 3.2 Neural Net Architecture. , 3.3 Data Augmentation.

Additional Edition: Print version: Mohanty, Mihir Narayan Meta Heuristic Techniques in Software Engineering and Its Applications Cham : Springer International Publishing AG,c2022 ISBN 9783031117121

Language: English