الصفحة 33
الصفحة 33
Markov Chains : Models, Algorithms and Applications
Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.
Manufacturing Execution Systems - MES
The production plants of today develop into modern service centers. Economic efficiency of modern added value is not a property of products alone but of the process. Decisive potential in business now is a question of process capability, rather than production capability. Process capability in business requires real-time systems for optimization. Business-IT needs to be developed from telecommunications and ERP to real time services, which are not offered by the prevailing ERP systems. Today, only modern Manufacturing Execution Systems (MES) offer real-time applications. They generate current as well as historic mappings of production facilities and thus they can be used as basis for optimizations. It is important to map the supply chain in real time. Increasing complexity in production requires an integrated view of the production and service facilities: detailed scheduling, status collection, quality, performance analysis, tracing of material and so on have to be recorded and displayed in an integrated way.
Managing Weather and Climate Risks in Agriculture
In many parts of the world, weather and climate are one of the biggest production risks and uncertainty factors impacting on agricultural systems performance and management. Both structural and non-structural measures can be used to reduce the impacts of the variability (including extremes) of climate resources on crop production. While the structural measures include strategies such as irrigation, water harvesting, windbreaks etc., the non-structural measures include use of seasonal to interannual climate forecasts, improved application of medium-range weather forecasts and crop insurance. This book based on an International Workshop held in New Delhi, India should be of interest to all organizations and agencies interested in improved risk management in agriculture.
Managing Traffic Performance in Converged Networks ; 20th International Teletraffic Congress, ITC20 2007, Ottawa, Canada, June 17-21, 2007, Proceedings
Managing traffic performance is a critical enabler for success. Reaching the desired performance levels requires adapting processes such as network planning, resource engineering, and network monitoring to the converged network milieu.
Managing Large-Scale Service Deployment ; 19th IFIP/IEEE International Workshop on Distributed Systems : Operations and Management, DSOM 2008, Samos Island, Greece, September 22-26, 2008. Proceedings
Contains all papers accepted for presentation at the 19th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management (DSOM 2008),which was held September 25-26, 2008 on the island of Samos, Greece. DSOM 2008 was the 19th event in a series of annual workshops. It followed in the footsteps of previous s- cessful meetings, the most recent of which were held in San Jos´ e, California, USA (DSOM 2007), Dublin, Ireland (DSOM 2006), Barcelona, Spain (DSOM 2005), Davis, California, USA (DSOM 2004), Heidelberg, Germany (DSOM 2003), and Montreal, Canada (DSOM 2002).
Managing Complexity : Insights, Concepts, Applications
Each chapter in Managing Complexity focuses on analyzing real-world complex systems and transferring knowledge from the complex-systems sciences to applications in business, industry and society. The interdisciplinary contributions range from markets and production through logistics, traffic control, and critical infrastructures, up to network design, information systems, social conflicts and building consensus. They serve to raise readers' awareness concerning the often counter-intuitive behavior of complex systems and to help them integrate insights gained in complexity research into everyday planning, decision making, strategic optimization, and policy.
Managing Closed-Loop Supply Chains
Introduction Closing supply chains refers to taking care of items once they are no longer desired or can no longer be used by their user. Smart management of closed-loop supply chains means profitable recovery of value from these items (products, functional components, materials or packaging). The company closing the supply chain may be the original equipment manuf- turer (OEM), a distribution partner or a third party not involved in the f- ward distribution. In recent years, the management of closed-loop supply chains has gained importance because of increased legislation on producer respon- bility, requiring companies to take back products from customers and to organize for proper recovery and disposal. This legislation is partially due to increased awareness of environmental issues. However, smart com- nies have also understood that returned products often contain lots of value to be recovered. They manage closed-loop supply chains simply because it is a profitable business proposition.
Malliavin Calculus for Lévy Processes with Applications to Finance
While the original works on Malliavin calculus aimed to study the smoothness of densities of solutions to stochastic differential equations, this book has another goal. It portrays the most important and innovative applications in stochastic control and finance, such as hedging in complete and incomplete markets, optimisation in the presence of asymmetric information and also pricing and sensitivity analysis. In a self-contained fashion, both the Malliavin calculus with respect to Brownian motion and general Lévy type of noise are treated. Besides, forward integration is included and indeed extended to general Lévy processes. The forward integration is a recent development within anticipative stochastic calculus that, together with the Malliavin calculus, provides new methods for the study of insider trading problems.
Machining: Fundamentals and Recent Advances
Machining is one of the most important manufacturing processes. Parts manufactured by others processes often require further operations before the product is ready for application. Machining is the broad term used to describe the removal of material from a work-piece. Machining processes can be applied to work metallic and non-metallic materials such as polymers, wood, ceramics and composites.
Machine-learning-assisted intelligent processing and optimization of complex systems
Focuses on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling
Machine Learning: ECML 2007 ; 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings
The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the ?rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was?rstheldin1997inTrondheim, Norway.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine learning and data mining for sports analytics ; 7th international workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
Constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.
Machine Learning and Big Data Analytics Paradigms : Analysis, Applications and Challenges
Intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.
Machine learning and big data : Concepts, algorithms, tools and applications
Showcase novel use-cases and applications, present empirical research results from user-centered qualitative and quantitative experiments of these new applications, and facilitate a discussion forum to explore the latest trends in big data and machine learning by providing algorithms which can be trained to perform interdisciplinary techniques such as statistics, linear algebra, and optimization and also create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention
Machine Learning : The Basics
Approaches ML as the computational implementation of the scientific principle. This principle consists of continuously adapting a model of a given data-generating phenomenon by minimizing some form of loss incurred by its predictions. Trains readers to break down various ML applications and methods in terms of data, model, and loss, thus helping them to choose from the vast range of ready-made ML methods.
Low-Power High-Level Synthesis for Nanoscale CMOS Circuits
Low-Power High-Level Synthesis for Nanoscale CMOS Circuits addresses the need for analysis, characterization, estimation, and optimization of the various forms of power dissipation in the presence of process variations of nano-CMOS technologies. The authors show very large-scale integration (VLSI) researchers and engineers how to minimize the different types of power consumption of digital circuits.
Logistics Systems Analysis
It has two new sections, a new appendix, and more than half a dozen new figures. A few references have also been added, Much of the new material is based on work , The financial support of the National Science Foundation and the Volvo Foundations Center of Excellence for the Future of Urban Transportation at U. C. Berkeley is also acknowledged. The new appendix presents the logic behind the traveling salesman and vehicle routing results used in Sec. 4. 2 to describe the transportation ope- tion; Chapter 4 is more self-contained as a result. New section 5. 6 int- duces and evaluates a general method that automatically translates the c- tinuum approximation recipes of Chapters 4 and 5 into discrete system designs. This closes a gap in previous editions. Other additions include an explanation of how to develop system designs that can efficiently acc- modate real-time control strategies to manage uncertainty (new section 4. 6. 3), and extensions of the many-to-many design ideas of Chap. 6
Logistics Systems : Design and Optimization
In a context of global competition, the optimization of logistics systems is inescapable. LOGISTICS SYSTEMS: Design and Optimization falls within this perspective and presents twelve chapters that well illustrate the variety and the complexity of logistics activities. Each chapter is written by recognized researchers who have been commissioned to survey a specific topic or emerging area of logistics. The first chapter, by Riopel, Langevin, and Campbell, develops a framework for the entire book. It classifies logistics decisions and highlights the relevant linkages to logistics decisions. The intricacy of these linkages demonstrates how thoroughly the decisions are interrelated and underscores the complexity of managing logistics activities. Each of the following chapters focus on quantitative methods for the design and optimization of logistics systems.
Logic-Based Program Synthesis and Transformation ; 17th International Symposium, LOPSTR 2007, Kongens Lyngby, Denmark, August 23-24, 2007, Revised Selected Papers
Contains a selectionofthe the paperspresentedatthe 17thInter- tional Symposium on Logic-Based Program Synthesis and Transformation, that was held in Kongens Lyngby, Denmark, August 23-24,2007. LOPSTR thus traditionally solicits papers in the areas of: specification, synthesis, verification, transformation, analysis, optimization, composition, security, reuse, applications andtools, component-baseds of tware development, software architectures, age- based software development and program refnement. Formal proceedings are produced only after the symposium, so that authors can incorporate this feed back in the published papers.
