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Author: Dr. Parveen Chauhan
Publisher: Xoffencerpublication
ISBN: 811953428X
Category : Business & Economics
Languages : en
Pages : 303
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Book Description
The concept of fuzzy logic refers to a specific subset of many-valued logic. In this line of reasoning, the truth value of a variable can be any real integer, including any fraction that is between 0 and 1. This applies to all fractions as well. It achieves this by regulating the concept of partial truth, in which the truth value may switch between being entirely true and entirely false at any given moment. This objective may be accomplished by making use of the tool for managing concepts. In contrast, the truth values of variables in Boolean logic can never be anything other than the integer values 0 or 1, as there are only two alternatives that even have a remote chance of occurring. This is because there are only two options that are even remotely imaginable. It is common practice to consider the fuzzy set theory, which was created in 1965 by the Iranian-Azerbaijani mathematician Lotfi Zadeh, to be the basis for fuzzy logic. However, since the 1920s, scholars have been investigating fuzzy logic, which was also known as infinite-valued logic at the time. Most notably, Lukasiewicz and Tarski were the researchers that began this line of inquiry. This particular investigation didn't wrap up until the 1960s, but it began in the 1920s. The idea of fuzzy logic is based on the fact that decision-makers frequently rely on hazy and non-numerical information. In other words, this is the origin of fuzzy logic. The mathematical methods of fuzzy modeling and fuzzy set creation, both of which are used to describe ambiguous and imprecise information, are where the name "fuzzy" first appeared. These models are capable of recognizing, representing, manipulating, understanding, and using facts and information that are fundamentally hazy and ambiguous in nature. Fuzzy logic has been effectively applied in a variety of applications, from control theory to artificial intelligence. Conventional patterns of thinking can only ever lead to conclusions that are either correct or incorrect. However, there are other statements that may elicit a range of responses, such as the answers you could get if you asked a group of individuals to name a color. One that invites people to name a meal is another 1 | P a ge illustration of this kind of proposal. In situations like this, it is the application of reasoning based on incomplete or inaccurate information that leads to the finding of the truth. This argument entails plotting the sampled responses on a spectrum. Although degrees of truth and probabilities both range from 0 to 1, fuzzy logic employs degrees of truth as a mathematical model of ambiguity whereas probability is a mathematical model of ignorance, despite the fact that they may initially appear to be the same. Although they could at first glance appear to be the same because both probability and degrees of truth range from 0 to 1, this is only because they do.
Author: Dr. Parveen Chauhan
Publisher: Xoffencerpublication
ISBN: 811953428X
Category : Business & Economics
Languages : en
Pages : 303
Get Book Here
Book Description
The concept of fuzzy logic refers to a specific subset of many-valued logic. In this line of reasoning, the truth value of a variable can be any real integer, including any fraction that is between 0 and 1. This applies to all fractions as well. It achieves this by regulating the concept of partial truth, in which the truth value may switch between being entirely true and entirely false at any given moment. This objective may be accomplished by making use of the tool for managing concepts. In contrast, the truth values of variables in Boolean logic can never be anything other than the integer values 0 or 1, as there are only two alternatives that even have a remote chance of occurring. This is because there are only two options that are even remotely imaginable. It is common practice to consider the fuzzy set theory, which was created in 1965 by the Iranian-Azerbaijani mathematician Lotfi Zadeh, to be the basis for fuzzy logic. However, since the 1920s, scholars have been investigating fuzzy logic, which was also known as infinite-valued logic at the time. Most notably, Lukasiewicz and Tarski were the researchers that began this line of inquiry. This particular investigation didn't wrap up until the 1960s, but it began in the 1920s. The idea of fuzzy logic is based on the fact that decision-makers frequently rely on hazy and non-numerical information. In other words, this is the origin of fuzzy logic. The mathematical methods of fuzzy modeling and fuzzy set creation, both of which are used to describe ambiguous and imprecise information, are where the name "fuzzy" first appeared. These models are capable of recognizing, representing, manipulating, understanding, and using facts and information that are fundamentally hazy and ambiguous in nature. Fuzzy logic has been effectively applied in a variety of applications, from control theory to artificial intelligence. Conventional patterns of thinking can only ever lead to conclusions that are either correct or incorrect. However, there are other statements that may elicit a range of responses, such as the answers you could get if you asked a group of individuals to name a color. One that invites people to name a meal is another 1 | P a ge illustration of this kind of proposal. In situations like this, it is the application of reasoning based on incomplete or inaccurate information that leads to the finding of the truth. This argument entails plotting the sampled responses on a spectrum. Although degrees of truth and probabilities both range from 0 to 1, fuzzy logic employs degrees of truth as a mathematical model of ambiguity whereas probability is a mathematical model of ignorance, despite the fact that they may initially appear to be the same. Although they could at first glance appear to be the same because both probability and degrees of truth range from 0 to 1, this is only because they do.
Author: Wang, John
Publisher: IGI Global
ISBN: 1466652039
Category : Business & Economics
Languages : en
Pages : 2862
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Book Description
As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.
Author: Cengiz Kahraman
Publisher: Springer
ISBN: 3030237567
Category : Technology & Engineering
Languages : en
Pages : 1386
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Book Description
This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.
Author: Ajith Abraham
Publisher: Springer Nature
ISBN: 3030963020
Category : Technology & Engineering
Languages : en
Pages : 705
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Book Description
This book highlights the recent research on soft computing, pattern recognition, nature-inspired computing and their various practical applications. It presents 53 selected papers from the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021) and 11 papers from the 13th World Congress on Nature and Biologically Inspired Computing (NaBIC 2021), which was held online, from December 15 to 17, 2021. A premier conference in the field of soft computing, artificial intelligence and machine learning applications, SoCPaR-NaBIC 2021 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from over 20 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of computer science and engineering.
Author: Foued Saâdaoui
Publisher: Springer Nature
ISBN: 3031365704
Category : Business & Economics
Languages : en
Pages : 338
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Book Description
This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance. It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies. The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks
Author: Bhatnagar, Vishal
Publisher: IGI Global
ISBN: 1466642149
Category : Computers
Languages : en
Pages : 412
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Book Description
Many organizations, whether in the public or private sector, have begun to take advantage of the tools and techniques used for data mining. Utilizing data mining tools, these organizations are able to reveal the hidden and unknown information from available data. Data Mining in Dynamic Social Networks and Fuzzy Systems brings together research on the latest trends and patterns of data mining tools and techniques in dynamic social networks and fuzzy systems. With these improved modern techniques of data mining, this publication aims to provide insight and support to researchers and professionals concerned with the management of expertise, knowledge, information, and organizational development.
Author: Amit V. Deokar
Publisher: Springer
ISBN: 3319580973
Category : Computers
Languages : en
Pages : 299
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Book Description
This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.
Author: Aljawarneh, Shadi
Publisher: IGI Global
ISBN: 1799850412
Category : Computers
Languages : en
Pages : 263
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Book Description
Cloud computing provides an easier alternative for starting an IT-based business organization that requires much less of an initial investment. Cloud computing offers a significant edge of traditional computing with big data being continuously transferred to the cloud. For extraction of relevant data, cloud business intelligence must be utilized. Cloud-based tools, such as customer relationship management (CRM), Salesforce, and Dropbox are increasingly being integrated by enterprises looking to increase their agility and efficiency. Impacts and Challenges of Cloud Business Intelligence is a cutting-edge scholarly resource that provides comprehensive research on business intelligence in cloud computing and explores its applications in conjunction with other tools. Highlighting a wide range of topics including swarm intelligence, algorithms, and cloud analytics, this book is essential for entrepreneurs, IT professionals, managers, business professionals, practitioners, researchers, academicians, and students.
Author: Dirk P. Kroese
Publisher: CRC Press
ISBN: 1000730778
Category : Business & Economics
Languages : en
Pages : 538
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Book Description
Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code
Author: Daniel Alejandro Rossit
Publisher: Elsevier
ISBN: 0443216509
Category : Science
Languages : en
Pages : 286
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Book Description
Evolution and Trends of Sustainable Approaches: Latest Development and Innovations in Science and Technology Applications provides different trends and approaches within the sustainability framework to assess their impact and offer possible solutions to problems facing the global sustainability paradigm. This book evaluates sustainability assessment approaches which support different levels of both decision-making and policy processes, thereby improving the management of natural and human systems. This book explores sustainable firm solutions, the upward trend of sustainability, and its variants. At the same time, different existing approaches are analyzed. These sustainable assessment approaches can be applied to products, services and technologies as well as business models, such as the Product-Service-System (PSS), Circular Economy (CE), Industrial Symbiosis (IS), and Supply Chain (SC). Finally, the book explores Sustainability Indicators (SIs), which are widely used to measure and communicate progress towards sustainable development, along with Life Cycle Sustainability Assessment (LCSA), balancing the three dimensions of sustainability (environmental, social and economic). - Explores innovative strategies and advanced trends of sustainable approaches, engineering, and industrial applications - Analyzes sustainability assessments and their role in planning and project processes - Reviews state-of-the-art sustainable technologies - Evaluates approaches for organizations to achieve both sustainability assessment and sustainable solutions
