Automating business modelling : A guide to using logic to represent Informal methods and support reasoning
Enterprise Modelling (EM) methods are frequently used by entrepreneurs as an analysis tool for describing and redesigning their businesses. The resulting product, an enterprise model, is commonly used as a blueprint for reconstructing organizations and such effort is often a part of business process re-engineering and improvement initiatives. Automating Business Modelling describes different techniques of providing automated support for enterprise modelling methods and introduces universally used approaches. A running example of a business modelling method is included; providing a framework and detailed explanation as to how to construct automated support for modelling, allowing readers to follow the method to create similar support. Suitable for senior undergraduates and postgraduates of Business Studies, Computer Science and Artificial Intelligence, practitioners in the fields of Knowledge Management, Enterprise Modelling and Software Engineering, this book offers insight and know-how to both student and professional.
كتب مشابهة
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
AI in banking : Practical applications and case studies
Delves into the application of AI from theory to practice, offering detailed insights into AI project design and code implementation across eleven business scenarios in four major sectors: retail banking, e-banking, bank credit, and tech operations. it provides hands-on examples of various technologies, including automatic machine learning, integrated learning, graph computation, recommendation systems, causal inference, generative adversarial networks, supervised learning, unsupervised learning, computer vision, reinforcement learning, fuzzy control, automatic control, speech recognition, semantic understanding, bayesian networks, edge computing, and more. this book stands as a rare and practical guide to AI projects in the banking industry.
Machine learning for cyber-physical systems: selected papers from the international conference ML4CPS 2023
Contains selected papers from the international conference ML4CPS – Machine Learning for Cyber-Physical Systems, which was held in Hamburg (Germany), from 29 to 31 March 2023. Cyber-physical systems are adaptive and learning: they analyze their environment and, based on observations, learn patterns, associations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnostics. Machine learning is the key technology for these developments.
Layce (Image data poisoning) = لايس (تسميم بيانات الصور )
The ongoing growth of image generative artificial intelligence models was paved with existing drawings and art pieces by great artists both past and present, and while generative models are very useful and helpful, there is the issue of the origin of the datasets trained on, and the morality of usage regarding copyrights and artistic identity. A novel line of defense that helps artists and visual content creators actively protect their pieces emerged, dubbed Data Poisoning and it works by misleading Artificial Intelligence models that attempt to use a Poisoned Image for training, or as a reference, as the Poisoned Image will appear to the human eye identical to the original art piece, while the Artificial Intelligence model will be seeing a remarkably different image, causing generative models to generate false positive results when given a prompt poisoned by the author or when trained on data poisoned by the original owner. This study aims to study image data poisoning methods and technologies, and build an application containing multiple image models, and poisoning models as well, accompanied by a Community for artists to share art and interact with each other.
