Download or read book Bankruptcy Prediction through Soft Computing based Deep Learning Technique written by Arindam Chaudhuri and published by Springer. This book was released on 2017-12-01 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes complex hierarchical deep architectures (HDA) for predicting bankruptcy, a topical issue for business and corporate institutions that in the past has been tackled using statistical, market-based and machine-intelligence prediction models. The HDA are formed through fuzzy rough tensor deep staking networks (FRTDSN) with structured, hierarchical rough Bayesian (HRB) models. FRTDSN is formalized through TDSN and fuzzy rough sets, and HRB is formed by incorporating probabilistic rough sets in structured hierarchical Bayesian model. Then FRTDSN is integrated with HRB to form the compound FRTDSN-HRB model. HRB enhances the prediction accuracy of FRTDSN-HRB model. The experimental datasets are adopted from Korean construction companies and American and European non-financial companies, and the research presented focuses on the impact of choice of cut-off points, sampling procedures and business cycle on the accuracy of bankruptcy prediction models. The book also highlights the fact that misclassification can result in erroneous predictions leading to prohibitive costs to investors and the economy, and shows that choice of cut-off point and sampling procedures affect rankings of various models. It also suggests that empirical cut-off points estimated from training samples result in the lowest misclassification costs for all the models. The book confirms that FRTDSN-HRB achieves superior performance compared to other statistical and soft-computing models. The experimental results are given in terms of several important statistical parameters revolving different business cycles and sub-cycles for the datasets considered and are of immense benefit to researchers working in this area.
Download or read book Engineering Applications of Neural Networks written by John Macintyre and published by Springer. This book was released on 2019-05-14 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019. The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.
Download or read book Visual and Text Sentiment Analysis through Hierarchical Deep Learning Networks written by Arindam Chaudhuri and published by Springer. This book was released on 2019-04-06 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to date, but most of the current methods focus on either only textual content, or only visual content. In contrast, the proposed sentiment analysis model can be applied to any social blog dataset, making the book highly beneficial for postgraduate students and researchers in deep learning and sentiment analysis. The mathematical abstraction of the sentiment analysis model is presented in a very lucid manner. The complete sentiments are analysed by combining text and visual prediction results. The book’s novelty lies in its development of innovative hierarchical recurrent neural networks for analysing sentiments; stacking of multiple recurrent layers by controlling the signal flow from upper recurrent layers to lower layers through a global gating unit; evaluation of HGFRNNs with different types of recurrent units; and adaptive assignment of HGFRNN layers to different timescales. Considering the need to leverage large-scale social multimedia content for sentiment analysis, both state-of-the-art visual and textual sentiment analysis techniques are used for joint visual-textual sentiment analysis. The proposed method yields promising results from Twitter datasets that include both texts and images, which support the theoretical hypothesis.
Download or read book Artificial Intelligence for Air Quality Monitoring and Prediction written by Amit Awasthi and published by CRC Press. This book was released on 2024-10-02 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive overview of advancements in artificial intelligence (AI) and how it can be applied in the field of air quality management. It explains the linkage between conventional approaches used in air quality monitoring and AI techniques such as data collection and preprocessing, deep learning, machine vision, natural language processing, and ensemble methods. The integration of climate models and AI enables readers to understand the relationship between air quality and climate change. Different case studies demonstrate the application of various air monitoring and prediction methodologies and their effectiveness in addressing real-world air quality challenges. Features A thorough coverage of air quality monitoring and prediction techniques. In-depth evaluation of cutting-edge AI techniques such as machine learning and deep learning. Diverse global perspectives and approaches in air quality monitoring and prediction. Practical insights and real-world case studies from different monitoring and prediction techniques. Future directions and emerging trends in AI-driven air quality monitoring. This is a great resource for professionals, researchers, and students interested in air quality management and control in the fields of environmental science and engineering, atmospheric science and meteorology, data science, and AI.
Download or read book Earnings Management Fintech Driven Incentives and Sustainable Growth written by Michael I. C. Nwogugu and published by Routledge. This book was released on 2019-11-01 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional research about Financial Stability and Sustainable Growth typically omits Earnings Management (as a broad class of misconduct), Complex Systems Theory, Mechanism Design Theory, Public Health, psychology issues, and the externalities and psychological effects of Fintech. Inequality, Environmental Pollution, Earnings Management opportunities, the varieties of complex Financial Instruments, Fintech, Regulatory Fragmentation, Regulatory Capture and real-financial sector-linkages are growing around the world, and these factors can have symbiotic relationships. Within Complex System theory framework, this book analyzes these foregoing issues, and introduces new behaviour theories, Enforcement Dichotomies, and critiques of models, regulations and theories in several dimensions. The issues analyzed can affect markets, and evolutions of systems, decision-making, "nternal Markets and risk-perception within government regulators, operating companies and investment entities, and thus they have Public Policy implications. The legal analysis uses applicable US case-law and statutes (which have been copied by many countries, and are similar to those of many common-law countries). Using Qualitative Reasoning, Capital Dynamics Theory (a new approach introduced in this book), Critical Theory and elements of Mechanism Design Theory, the book aims to enhance cross-disciplinary analysis of the above-mentioned issues; and to help researchers build better systems/Artificial-Intelligence/mathematical models in Financial Stability, Portfolio Management, Policy-Analysis, Asset Pricing, Contract Theory, Enforcement Theory and Fraud Detection. The primary audience for this book consists of university Professors, PHD students and PHD degree-holders (in industries, government agencies, financial services companies and research institutes). The book can be used as a primary or supplementary textbook for graduate courses in Regulation; Capital Markets; Law & Economics, International Political Economy and or Mechanism Design (Applied Math, Operations Research, Computer Science or Finance).
Download or read book Soft Computing for Problem Solving written by Aruna Tiwari and published by Springer Nature. This book was released on 2021-10-13 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume book provides an insight into the 10th International Conference on Soft Computing for Problem Solving (SocProS 2020). This international conference is a joint technical collaboration of Soft Computing Research Society and Indian Institute of Technology Indore. The book presents the latest achievements and innovations in the interdisciplinary areas of soft computing. It brings together the researchers, engineers and practitioners to discuss thought-provoking developments and challenges, in order to select potential future directions. It covers original research papers in the areas including but not limited to algorithms (artificial immune system, artificial neural network, genetic algorithm, genetic programming and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). The book will be beneficial for young as well as experienced researchers dealing across complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.
Download or read book Soft Computing Theories and Applications written by Tarun K. Sharma and published by Springer Nature. This book was released on 2021-06-26 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2020), organized online. The book is divided into two volumes and offers valuable insights into soft computing for teachers and researchers alike; the book will inspire further research in this dynamic field.
Download or read book Novel Financial Applications of Machine Learning and Deep Learning written by Mohammad Zoynul Abedin and published by Springer Nature. This book was released on 2023-03-01 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study. The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice. The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Download or read book Artificial Intelligence and Soft Computing written by Leszek Rutkowski and published by Springer. This book was released on 2018-05-24 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 10841 and LNAI 10842 constitutes the refereed proceedings of the 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018, held in Zakopane, Poland in June 2018. The 140 revised full papers presented were carefully reviewed and selected from 242 submissions. The papers included in the second volume are organized in the following five parts: computer vision, image and speech analysis; bioinformatics, biometrics, and medical applications; data mining; artificial intelligence in modeling, simulation and control; and various problems of artificial intelligence.
Download or read book Advances in Entrepreneurial Finance written by Rassoul Yazdipour and published by Springer Science & Business Media. This book was released on 2010-12-17 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Entrepreneurial Finance brings together contributions from researchers from the fields of entrepreneurship, behavioral finance, psychology, and neuroscience to shed new light on the dynamics of decision making and risk taking by entrepreneurs and venture capitalists (VCs). Every new venture requires access to capital at competitive interest rates, and much has been written on general entrepreneurship by management scholars and financial contracting by financial economists using traditional finance theory with all its highly restrictive assumptions regarding decision makers’ cognitive capabilities and behavior. But recent developments in behavioral finance can now be applied to understand how entrepreneurs and VCs perceive risk and uncertainty and how they decide and act accordingly. Showcasing the latest research, this volume demonstrates that findings from the behavioral and neuroscience arenas can and do explain decision making by entrepreneurs and venture investors in the real world. Consequently, such findings have practical implications not only for entrepreneurs, venture capitalists, and their advisors, but also all government agencies and NGOs that want to support product and technological innovation, capital formation, job creation, and economic development.
Download or read book Business Intelligence in Economic Forecasting Technologies and Techniques written by Wang, Jue and published by IGI Global. This book was released on 2010-06-30 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid development of economic globalization and information technology, the field of economic forecasting continues its expeditious advancement, providing business and government with applicable technologies. This book discusses various business intelligence techniques including neural networks, support vector machine, genetic programming, clustering analysis, TEI@I, fuzzy systems, text mining, and many more. It serves as a valuable reference for professionals and researchers interested in BI technologies and their practical applications in economic forecasting, as well as policy makers in business organizations and governments.
Download or read book An Analysis of Features Predicting Bankruptcy of Newly Formed Japanese Small and Medium Sized Firms Using Machine Learning Techniques written by Hong Xu and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The study analyses the bankruptcy of newly formed Japanese small and medium-sized entities (SMEs) by comparing specific features with newly formed but survived SMEs. It applies Resource-based Firm Theory and other theories to identify the bankruptcy features and uses logit regression to validate those features. It builds bankruptcy prediction models using machine learning techniques based on those features and evaluates the performance of the models.
Download or read book Artificial Intelligence in Financial Markets written by Christian L. Dunis and published by Springer. This book was released on 2016-11-21 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Download or read book Soft Computing Techniques in Engineering Health Mathematical and Social Sciences written by Pradip Debnath and published by CRC Press. This book was released on 2021-07-15 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing techniques are no longer limited to the arena of computer science. The discipline has an exponentially growing demand in other branches of science and engineering and even into health and social science. This book contains theory and applications of soft computing in engineering, health, and social and applied sciences. Different soft computing techniques such as artificial neural networks, fuzzy systems, evolutionary algorithms and hybrid systems are discussed. It also contains important chapters in machine learning and clustering. This book presents a survey of the existing knowledge and also the current state of art development through original new contributions from the researchers. This book may be used as a one-stop reference book for a broad range of readers worldwide interested in soft computing. In each chapter, the preliminaries have been presented first and then the advanced discussion takes place. Learners and researchers from a wide variety of backgrounds will find several useful tools and techniques to develop their soft computing skills. This book is meant for graduate students, faculty and researchers willing to expand their knowledge in any branch of soft computing. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics.
Download or read book Artificial Intelligence Theories Models and Applications written by Ilias Maglogiannis and published by Springer. This book was released on 2012-05-26 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th Hellenic Conference on Artificial Intelligence, SETN 2012, held in Lamia, Greece, in May 2012. The 47 contributions included in this volume were carefully reviewed and selected from 81 submissions. They deal with emergent topics of artificial intelligence and come from the SETN main conference as well as from the following special sessions on advancing translational biological research through the incorporation of artificial intelligence methodologies; artificial intelligence in bioinformatics; intelligent annotation of digital content; intelligent, affective, and natural interfaces; and unified multimedia knowledge representation and processing.
Download or read book Soft Computing Methodologies for Bankruptcy Prediction written by Nidhi Arora and published by . This book was released on 2017-03-14 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive and Natural Computing Algorithms written by Marco Tomassini and published by Springer. This book was released on 2013-04-12 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book constitutes the refereed proceedings of the 11th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2013, held in Lausanne, Switzerland, in April 2013. The 51 revised full papers presented were carefully reviewed and selected from a total of 91 submissions. The papers are organized in topical sections on neural networks, evolutionary computation, soft computing, bioinformatics and computational biology, advanced computing, and applications.