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Author: Arturo Hernández Aguirre
Publisher: Springer Science & Business Media
ISBN: 3642052576
Category : Computers
Languages : en
Pages : 759
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Book Description
This book constitutes the refereed proceedings of the 8th Mexican International Conference on Artificial Intelligence, MICAI 2009, held in Guanajuato, Mexico, in November 2009. The 63 revised full papers presented together with one invited talk were carefully reviewed and selected from 215 submissions. The papers are organized in topical sections on logic and reasoning, ontologies, knowledge management and knowledge-based systems, uncertainty and probabilistic reasoning, natural language processing, data mining, machine learning, pattern recognition, computer vision and image processing, robotics, planning and scheduling, fuzzy logic, neural networks, intelligent tutoring systems, bioinformatics and medical applications, hybrid intelligent systems and evolutionary algorithms.
Author: Arturo Hernández Aguirre
Publisher: Springer Science & Business Media
ISBN: 3642052576
Category : Computers
Languages : en
Pages : 759
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 8th Mexican International Conference on Artificial Intelligence, MICAI 2009, held in Guanajuato, Mexico, in November 2009. The 63 revised full papers presented together with one invited talk were carefully reviewed and selected from 215 submissions. The papers are organized in topical sections on logic and reasoning, ontologies, knowledge management and knowledge-based systems, uncertainty and probabilistic reasoning, natural language processing, data mining, machine learning, pattern recognition, computer vision and image processing, robotics, planning and scheduling, fuzzy logic, neural networks, intelligent tutoring systems, bioinformatics and medical applications, hybrid intelligent systems and evolutionary algorithms.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 120
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Book Description
Papers presented at this session include: recent developments and potential future directions in ranking and optimization procedures for pavement management (cook, wd and lytton, rl); sample size selection (scullion, t, lytton, rl and templeton, cj); the economic optimization of pavement maintenance and rehabilitation policy (markow, mj, brademeyer, bd and sherwood, j); achieving efficiency in planning and programming through network-level policy optimization and pavement management (paterson, wdo and fossberg, pe); a dynamic programming approach to optimization for pavement management systems (feighan, kj, shahin, my and sinha, kc); a decomposition approach for rehabilitation and maintenance programming (gendreau, m); a computationally efficient system for infrastructure management with application to pavement management (nesbitt, dm and sparks, ga); a micro-computer markov dynamic programming system for pavement management in finland (thompson, pd, neumann, la and miettinen, m). for the covering abstract of the conference see irrd 807044.
Author: Kathryn A. Zimmerman
Publisher: Transportation Research Board
ISBN: 9780309058667
Category : Technology & Engineering
Languages : en
Pages : 108
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Book Description
This synthesis will be of interest to highway administrators; pavement management system (PMS), maintenance, and computer engineers; and technologists involved with data collection and computer programming for the purposes of a PMS. This synthesis describes the state of the practice with respect to pavement management methodologies to select projects and recommend preservation treatments. This report of the Transportation Research Board also describes the predominant pavement management methodologies being used by U.S. state and Canadian provincial transportation agencies; provides a general description of each methodology; and summarizes the requirements, benefits, hindrances, and constraints associated with each. It includes a review of domestic literature and a survey of current practices in North America. In addition, case studies are included to illustrate the use of these methodologies within transportation agencies. Operational and soon-to-be implemented technologies are also discussed, and an extensive bibliography is provided for further reference.
Author: De-Shuang Huang
Publisher: Springer
ISBN: 3319633155
Category : Computers
Languages : en
Pages : 781
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Book Description
This three-volume set LNCS 10361, LNCS 10362, and LNAI 10363 constitutes the refereed proceedings of the 13th International Conference on Intelligent Computing, ICIC 2017, held in Liverpool, UK, in August 2017. The 212 full papers and 20 short papers of the three proceedings volumes were carefully reviewed and selected from 612 submissions. This third volume of the set comprises 67 papers. The papers are organized in topical sections such as Intelligent Computing in Robotics; Intelligent Computing in Computer Vision; Intelligent Control and Automation; Intelligent Agent and Web Applications; Fuzzy Theory and Algorithms; Supervised Learning; Unsupervised Learning; Kernel Methods and Supporting Vector Machines; Knowledge Discovery and Data Mining; Natural Language Processing and Computational Linguistics; Advances of Soft Computing: Algorithms and Its Applications - Rozaida Ghazali; Advances in Swarm Intelligence Algorithm; Computational Intelligence and Security for Image Applications in SocialNetwork; Biomedical Image Analysis; Information Security; Machine Learning; Intelligent Data Analysis and Prediction.
Author: K.S. Tang
Publisher: CRC Press
ISBN: 1439899215
Category : Science
Languages : en
Pages : 266
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Book Description
The first book to focus on jumping genes outside bioscience and medicine, Multiobjective Optimization Methodology: A Jumping Gene Approach introduces jumping gene algorithms designed to supply adequate, viable solutions to multiobjective problems quickly and with low computational cost. Better Convergence and a Wider Spread of Nondominated Solutions The book begins with a thorough review of state-of-the-art multiobjective optimization techniques. For readers who may not be familiar with the bioscience behind the jumping gene, it then outlines the basic biological gene transposition process and explains the translation of the copy-and-paste and cut-and-paste operations into a computable language. To justify the scientific standing of the jumping genes algorithms, the book provides rigorous mathematical derivations of the jumping genes operations based on schema theory. It also discusses a number of convergence and diversity performance metrics for measuring the usefulness of the algorithms. Practical Applications of Jumping Gene Algorithms Three practical engineering applications showcase the effectiveness of the jumping gene algorithms in terms of the crucial trade-off between convergence and diversity. The examples deal with the placement of radio-to-fiber repeaters in wireless local-loop systems, the management of resources in WCDMA systems, and the placement of base stations in wireless local-area networks. Offering insight into multiobjective optimization, the authors show how jumping gene algorithms are a useful addition to existing evolutionary algorithms, particularly to obtain quick convergence solutions and solutions to outliers.
Author: Milan Vojnović
Publisher: Cambridge University Press
ISBN: 1316472906
Category : Computers
Languages : en
Pages : 737
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Book Description
Contests are prevalent in many areas, including sports, rent seeking, patent races, innovation inducement, labor markets, scientific projects, crowdsourcing and other online services, and allocation of computer system resources. This book provides unified, comprehensive coverage of contest theory as developed in economics, computer science, and statistics, with a focus on online services applications, allowing professionals, researchers and students to learn about the underlying theoretical principles and to test them in practice. The book sets contest design in a game-theoretic framework that can be used to model a wide-range of problems and efficiency measures such as total and individual output and social welfare, and offers insight into how the structure of prizes relates to desired contest design objectives. Methods for rating the skills and ranking of players are presented, as are proportional allocation and similar allocation mechanisms, simultaneous contests, sharing utility of productive activities, sequential contests, and tournaments.
Author: Erick Moreno Centeno
Publisher:
ISBN:
Category :
Languages : en
Pages : 206
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Book Description
This dissertation addresses important problems in decision theory and data mining. In particular, we focus on problems of the form: Each of several information sources provides evaluations or measurements of the objects in a universal set, and the objective is to aggregate these, possibly conflicting, evaluations into a consensus evaluation of each object in the universal set. In addition, we concentrate on the scenario where each source provides evaluations of only a strict subset of the objects; that is, each source provides an incomplete evaluation. In order to define the consensus evaluation from a given set of incomplete evaluations, two distances are developed: the first is a distance between incomplete rankings (ordinal evaluations) and the second is a distance between incomplete ratings (cardinal evaluations). These two distances generalize Kemeny and Snell's distance between complete rankings and Cook and Kress' distance between complete ratings, respectively. Specifically, we introduce a set of natural axioms that must be satisfied by a distance between two incomplete rankings (ratings) and prove the uniqueness and existence of a distance satisfying such axioms. Given a set of incomplete rankings (ratings), the consensus ranking (rating) is defined as the complete ranking (rating) that minimizes the sum of distances to each of the given rankings (ratings). We provide several examples that show that the consensus ranking (rating) obtained by this approach is more intuitive than that obtained by other approaches. Finding the consensus ranking is NP-hard, thus we develop two optimization methodologies to find the consensus ranking: one efficient approximation algorithm based on the separation-deviation model and one exact algorithm based on the implicit hitting set approach. In addition, we show that the optimization problem that needs to be solved in order to find the consensus rating is a special case of the separation-deviation model (hereafter SD model), which is solvable in polynomial time. In this sense, the herein developed theory (described in the previous paragraph) can be thought of an axiomatization of the SD model. Three applications of the SD model are presented: rating the credit-risk of countries; customer segmentation; and ranking the participants in a student paper competition. In the credit-risk rating study, it is shown that the SD model leads to an improved aggregate rating with respect to several criteria. We compare the SD model with other aggregation methods and show the following: Although the SD model is a method to aggregate cardinal evaluations, the aggregate credit-risk ratings obtained by the SD model are also good with respect to "ordinal criteria". Several properties of the SD model are proven, including the property that the aggregate rating obtained by the SD model agrees with the majority of agencies or reviewers, regardless of the scale used. The customer segmentation study shows how to use the SD model to process data on customer purchasing timing. The outcome of the SD model provides insights on the rate of new product adoption by the company's consumers. In particular, the SD model is used as follows: given the purchase dates for each customer of several products, this information is aggregated in order to rate the customers with regard to their promptness to adopt new technology. We show that this approach outperforms unidimensional scaling--a widely used data mining methodology. We analyze the results with respect to various dimensions of the customer base and report on the generated insights. The last presented application illustrates our aggregation methods in the context of the 2007 MSOM's student paper competition. The aggregation problem in this competition poses two challenges. First, each paper was reviewed only by a very small fraction of the judges; thus the aggregate evaluation is highly sensitive to the subjective scales chosen by the judges. Second, the judges provided both cardinal and ordinal evaluations (ratings and rankings) of the papers they reviewed. This chapter develops the first known methodology to simultaneously aggregate ordinal and cardinal evaluations into a consensus evaluation. Although the content of this dissertation is framed in terms of decision theory, Hochbaum showed that data mining problems can be viewed as special cases of decision theory problems. In particular, the customer segmentation study is a classic data mining problem.
Author: Tilahun, Surafel Luleseged
Publisher: IGI Global
ISBN: 1522550925
Category : Computers
Languages : en
Pages : 327
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Book Description
When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects. Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.
Author: Xin-She Yang
Publisher: John Wiley & Sons
ISBN: 1119490545
Category : Mathematics
Languages : en
Pages : 384
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Book Description
A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.
Author: Kegesa Danvas Abdullah
Publisher:
ISBN: 9781549579837
Category :
Languages : en
Pages : 106
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Book Description
This step by step SEO guide on ranking signals is easy to read, easy to follow, easy to implement.It has no fluff, it is affordable stuff.You shall learn more than 204 secrets of staying in the first page of Google for your perfectly chosen keywords. Google publicly stated that they "use over 200 factors to rank websites".You now have no excuse; you got to rank high in SERPs. Familiarize yourself with these strategies and you shall rank your website at the top of Google whether you are a beginner of an SEO expert.This e-book has helped me rank and grow various company websites online through white hat search engine optimization techniquesThe exact steps I used to rank them in the first page of Google are outlinedWith this book, you don't need anything else but a teachable spirit; marketing SEO will become child's play. If you have this book, you can do search engine optimization free of charge - SEO becomes a do it yourself thing. This is not a mere Google search engine optimization advice; these are actionable SEO tips that can change your life as you know it. The book captures all major Google updates and how to rank any website following the latest Google updates beyond 2017. Without taking your educational background into consideration, the book is so simple to implement since it lists the step by step process of doing white hat SEO that Google loves. It lays bare all SEO industry secrets that will help you stay ahead of Google algorithmic changes and achieve top rankings all the time.You will learn:The most important SEO techniques that will bring your site to the first page of GoogleSimple on-page factors that will help in boosting your PageRankWhite hat link building methods that Google lovesHow to avoid black hat SEO techniques that get sites punishedSEO tools that internet marketers use to rank websitesImportant content factors that will boost your rankingPage-Level Ranking Factors: How to use keywords in title tags, meta tags, description tags and H1, H2, H3, H4 tags to improve SEO. Site level-factors affecting search engine rankingDomain Factors of Search Engine optimization Backlink FactorsBrand SignalsSpecial Google Algorithm RulesOn-Site Web Spam Factors and SEOUser Interaction Signals and SEOEffects of Off-Page Web spam Factors in web rankingsEffects of Social Signals in SEOHow to use this e-book:Read the book once to the last page and pay attention to all SEO best practices checklistsDo a thorough website analysis by noting what you have not yet implemented. Stop wasting your precious timeImplement the secrets in this book and see your search engine results page rankings rise.Tell me your success or contact me directly to help you implement these website optimization tips and tricks.Implement the web page optimization best practices outlined in this ebook on a page by page basis. In case you have thin content, update it with high quality and useful content following the guide. Celebrate as your rankings grow.
