A Journey Towards Bio-inspired Techniques in Software Engineering PDF Download
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Author: Jagannath Singh
Publisher: Springer Nature
ISBN: 3030409287
Category : Technology & Engineering
Languages : en
Pages : 214
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Book Description
This book covers a range of basic and advanced topics in software engineering. The field has undergone several phases of change and improvement since its invention, and there is significant ongoing research in software development, addressing aspects such as analysis, design, testing and maintenance. Rather than focusing on a single aspect of software engineering, this book provides a systematic overview of recent techniques, including requirement gathering in the form of story points in agile software, and bio-inspired techniques for estimating the effort, cost, and time required for software development. As such it is a valuable resource for new researchers interested in advances in software engineering — particularly in the area of bio-inspired techniques.
Author: Jagannath Singh
Publisher: Springer Nature
ISBN: 3030409287
Category : Technology & Engineering
Languages : en
Pages : 214
Get Book Here
Book Description
This book covers a range of basic and advanced topics in software engineering. The field has undergone several phases of change and improvement since its invention, and there is significant ongoing research in software development, addressing aspects such as analysis, design, testing and maintenance. Rather than focusing on a single aspect of software engineering, this book provides a systematic overview of recent techniques, including requirement gathering in the form of story points in agile software, and bio-inspired techniques for estimating the effort, cost, and time required for software development. As such it is a valuable resource for new researchers interested in advances in software engineering — particularly in the area of bio-inspired techniques.
Author: Manju Khari
Publisher: Springer Nature
ISBN: 3031072979
Category : Technology & Engineering
Languages : en
Pages : 189
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Book Description
This book provides awareness of different evolutionary methods used for automatic generation and optimization of test data in the field of software testing. While the book highlights on the foundations of software testing techniques, it also focuses on contemporary topics for research and development. This book covers the automated process of testing in different levels like unit level, integration level, performance level, evaluation of testing strategies, testing in security level, optimizing test cases using various algorithms, and controlling and monitoring the testing process etc. This book aids young researchers in the field of optimization of automated software testing, provides academics with knowledge on the emerging field of AI in software development, and supports universities, research centers, and industries in new projects using AI in software testing. Supports the advancement in the artificial intelligence used in software development; Advances knowledge on artificial intelligence based metaheuristic approach in software testing; Encourages innovation in traditional software testing field using recent artificial intelligence. ·
Author: Jagannath Singh
Publisher: Springer Nature
ISBN: 9811968934
Category : Technology & Engineering
Languages : en
Pages : 176
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Book Description
The book constitutes proceedings of the 12th Industry Symposium held in conjunction with the 18th edition of the International Conference on Distributed Computing and Intelligent Technology (ICDCIT 2022). The focus of the industry symposium is on Mobile Application Development: Practice and Experience. This book focuses on software engineering research and practice supporting any aspects of mobile application development. The book discusses findings in the areas of mobile application analysis, models for generating these applications, testing, debugging & repair, localization & globalization, app review analytics, app store mining, app beyond smartphones and tablets, app deployment, maintenance, and reliability of apps, industrial case studies of automated software engineering for mobile apps, etc. Papers included in the book describe new or improved ways to handle these aspects or address them in a more unified manner, discussing benefits, limitations, and costs of provided solutions. The volume will be useful for master, research students as well as industry professionals.
Author: Osvaldo Gervasi
Publisher: Springer Nature
ISBN: 3030870073
Category : Computers
Languages : en
Pages : 748
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Book Description
The ten-volume set LNCS 12949 – 12958 constitutes the proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021, which was held in Cagliari, Italy, during September 13 – 16, 2021. The event was organized in a hybrid mode due to the Covid-19 pandemic.The 466 full and 18 short papers presented in these books were carefully reviewed and selected from 1588 submissions. Part VII of the set includes the proceedings of the following workshops: International Workshop on Geomatics for Resource Monitoring and Management (GRMM 2021); International Workshop on Geomatics in Agriculture and Forestry: new advances and perspectives (Geo-for-Agr 2021); 12th International Symposium on Software Quality (SQ 2021);10th International Workshop on Collective, Massive and Evolutionary Systems (IWCES 2021); International Workshop on Land Use monitoring for Sustainability (LUMS 2021); International Workshop on Machine Learning for Space and Earth Observation Data (MALSEOD 2021); International Workshop on Building multi-dimensional models for assessing complex environmental systems (MES 2021); International Workshop on Ecosystem Services: nature's contribution to people in practice. Assessment frameworks, models, mapping, andimplications (NC2P 2021).
Author: Sridaran Rajagopal
Publisher: Springer Nature
ISBN: 3031230957
Category : Computers
Languages : en
Pages : 317
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Book Description
This two-volume constitutes the refereed proceedings of the First International Conference on Advancements in Smart Computing and Information Security, ASCIS 2022, held in Rajkot, India, in November 2022. The 37 full papers and 19 short papers presented were thoroughly reviewed and selected from the 206 submissions. The papers are organized in topical sections on artificial intelligence; smart computing; cyber security; industry.
Author: Haldorai, Anandakumar
Publisher: IGI Global
ISBN: 1522597522
Category : Computers
Languages : en
Pages : 285
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Book Description
Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.
Author: Eyal Wirsansky
Publisher: Packt Publishing Ltd
ISBN: 1838559183
Category : Computers
Languages : en
Pages : 334
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Book Description
Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning models using Python libraries such as DEAP, scikit-learn, and NumPy Key Features Explore the ins and outs of genetic algorithms with this fast-paced guide Implement tasks such as feature selection, search optimization, and cluster analysis using Python Solve combinatorial problems, optimize functions, and enhance the performance of artificial intelligence applications Book DescriptionGenetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence. After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications. By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains.What you will learn Understand how to use state-of-the-art Python tools to create genetic algorithm-based applications Use genetic algorithms to optimize functions and solve planning and scheduling problems Enhance the performance of machine learning models and optimize deep learning network architecture Apply genetic algorithms to reinforcement learning tasks using OpenAI Gym Explore how images can be reconstructed using a set of semi-transparent shapes Discover other bio-inspired techniques, such as genetic programming and particle swarm optimization Who this book is for This book is for software developers, data scientists, and AI enthusiasts who want to use genetic algorithms to carry out intelligent tasks in their applications. Working knowledge of Python and basic knowledge of mathematics and computer science will help you get the most out of this book.
Author: Christian Heller
Publisher: CYBOP
ISBN: 3981089804
Category : Computer software
Languages : en
Pages : 537
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Book Description
Author: Eyal Wirsansky
Publisher: Packt Publishing Ltd
ISBN: 180512157X
Category : Computers
Languages : en
Pages : 419
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Book Description
Explore the ever-growing world of genetic algorithms to build and enhance AI applications involving search, optimization, machine learning, deep learning, NLP, and XAI using Python libraries Key Features Learn how to implement genetic algorithms using Python libraries DEAP, scikit-learn, and NumPy Take advantage of cloud computing technology to increase the performance of your solutions Discover bio-inspired algorithms such as particle swarm optimization (PSO) and NEAT Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorithms and neural networks, Hands-On Genetic Algorithms with Python offers expert insights and practical knowledge to master genetic algorithms. After an introduction to genetic algorithms and their principles of operation, you’ll find out how they differ from traditional algorithms and the types of problems they can solve, followed by applying them to search and optimization tasks such as planning, scheduling, gaming, and analytics. As you progress, you’ll delve into explainable AI and apply genetic algorithms to AI to improve machine learning and deep learning models, as well as tackle reinforcement learning and NLP tasks. This updated second edition further expands on applying genetic algorithms to NLP and XAI and speeding up genetic algorithms with concurrency and cloud computing. You’ll also get to grips with the NEAT algorithm. The book concludes with an image reconstruction project and other related technologies for future applications. By the end of this book, you’ll have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence with Python.What you will learn Use genetic algorithms to solve planning, scheduling, gaming, and analytics problems Create reinforcement learning, NLP, and explainable AI applications Enhance the performance of ML models and optimize deep learning architecture Deploy genetic algorithms using client-server architectures, enhancing scalability and computational efficiency Explore how images can be reconstructed using a set of semi-transparent shapes Delve into topics like elitism, niching, and multiplicity in genetic solutions to enhance optimization strategies and solution diversity Who this book is for If you’re a data scientist, software developer, AI enthusiast who wants to break into the world of genetic algorithms and apply them to real-world, intelligent applications as quickly as possible, this book is for you. Working knowledge of the Python programming language is required to get started with this book.
Author: Xin-She Yang
Publisher: Springer
ISBN: 3319676695
Category : Technology & Engineering
Languages : en
Pages : 332
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Book Description
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
