AI 企业级部署教程(机翻)

This book presents an introduction to MCDA followed by more detailed chapters about each of the leading methods used in this field. Comparison of methods and software is also featured to enable readers to choose the most appropriate method needed in their research. Worked examples as well as the software featured in the book are available on an accompanying website. 1.general Introduction -- 1.1.introduction -- 1.2.decision Problems -- 1.3.mcda Methods -- 1.4.mcda Software -- 1.5.selection Of Mcda Methods -- 1.6.outline Of The Book -- References -- Pt. I Full Aggregation Approach -- 2.analytic Hierarchy Process -- 2.1.introduction -- 2.2.essential Concepts Of Ahp -- 2.2.1.problem Structuring -- 2.2.2.priority Calculation -- 2.2.3.consistency Check -- 2.2.4.sensitivity Analysis -- 2.3.ahp Software: Makeitrational -- 2.3.1.problem Structuring -- 2.3.2.preferences And Priority Calculation -- 2.3.3.consistency Check -- 2.3.4.results -- 2.3.5.sensitivity Analysis -- 2.4.in The Black Box Of Ahp -- 2.4.1.problem Structuring -- 2.4.2.judgement Scales -- 2.4.3.consistency -- 2.4.4.priorities Derivation -- 2.4.5.aggregation -- 2.5.extensions Of Ahp -- 2.5.1.analytic Hierarchy Process Ordering -- 2.5.2.group Analytic Hierarchy Process -- 2.5.3.clusters And Pivots For A Large Number Of Alternatives -- 2.5.4.ahpsort 5.2.essential Concepts Of Macbeth -- 5.2.1.problem Structuring: Value Tree -- 5.2.2.score Calculation -- 5.2.3.incompatibility Check -- 5.3.software Description: M-macbeth -- 5.3.1.problem Structuring: Value Tree -- 5.3.2.evaluations And Scores -- 5.3.3.incompatibility Check -- 5.3.4.results -- 5.3.5.sensitivity Analysis -- 5.3.6.robustness Analysis -- 5.4.in The Black Box Of Macbeth -- 5.4.1.lp-macbeth -- 5.4.2.discussion -- References -- Pt. Ii Outranking Approach -- 6.promethee -- 6.1.introduction -- 6.2.essential Concepts Of The Promethee Method -- 6.2.1.unicriterion Preference Degrees -- 6.2.2.unicriterion Positive, Negative And Net Flows -- 6.2.3.global Flows -- 6.2.4.the Gaia Plane -- 6.2.5.sensitivity Analysis -- 6.3.the Smart Picker Pro Software -- 6.3.1.data Entry -- 6.3.2.entering Preference Parameters -- 6.3.3.weights -- 6.3.4.promethee Ii Ranking -- 6.3.5.gaia Plane -- 6.3.6.sensitivity Analysis -- 6.4.in The Black Box Of Promethee 6.4.1.unicriterion Preference Degrees -- 6.4.2.global Preference Degree -- 6.4.3.global Flows -- 6.4.4.promethee I And Promethee Ii Ranking -- 6.4.5.the Gaia Plane -- 6.4.6.influence Of Pairwise Comparisons -- 6.5.extensions Of Promethee -- 6.5.1.promethee Gdss -- 6.5.2.flowsort: A Sorting Or Supervised Classification Method -- References -- 7.electre -- 7.1.introduction -- 7.2.essentials Of The Electre Methods -- 7.2.1.electre Iii -- 7.3.the Electre Iii-iv Software -- 7.3.1.data Entry -- 7.3.2.entering Preference Parameters -- 7.3.3.results -- 7.4.in The Black Box Of Electre Iii -- 7.4.1.outranking Relations -- 7.4.2.partial Concordance Degree -- 7.4.3.global Concordance Degree -- 7.4.4.partial Discordance Degree -- 7.4.5.outranking Degree -- 7.4.6.partial Ranking: Exploitation Of The Outranking Relations -- 7.4.7.some Properties -- 7.5.electre-tri -- 7.5.1.introduction -- 7.5.2.preference Relations -- 7.5.3.assignment Rules -- 7.5.4.properties 10.4.2.variable Returns To Scale -- 10.5.extensions Of Dea -- 10.5.1.adjusting For The Environment -- 10.5.2.preferences -- 10.5.3.sensitivity Analysis -- 10.5.4.time Series Data -- References -- Pt. Iv Integrated Systems -- 11.multi-method Platforms -- 11.1.introduction -- 11.2.decision Deck -- 11.3.decerns -- 11.3.1.the Gis Module -- 11.3.2.the Mcda Module -- 11.3.3.the Gdss Module -- 11.3.4.integration -- References -- Appendix: Linear Optimization -- A.1.problem Modelling -- A.2.graphical Solution -- A.3.solution With Microsoft Excel. Alessio Ishizaka, Philippe Nemery. Includes Bibliographical References And Index. Mode Of Access: World Wide Web. Learn How To Develop And Employ An Ontology, The Secret Weapon For Successfully Using Artificial Intelligence To Create A Powerful Competitive Advantage In Your Business. The Ai-powered Enterprise Examines Two Fundamental Questions: First, How Will The Future Be Different As A Result Of Artificial Intelligence? And Second, What Must Companies Do To Stake Their Claim On That Future? When The Web Came Along In The Mid-90s, It Transformed The Behavior Of Customers And Remade Whole Industries. Now, As Part Of Its Promise To Bring Revolutionary Change In Untold Ways To Human Activity, Artificial Intelligence--ai--is About To Create Another Complete Transformation In How Companies Create And Deliver Value To Customers. But Despite The Billions Spent So Far On Bots And Other Tools, Ai Continues To Stumble. Why Can't It Magically Use All The Data Organizations Generate To Make Them Run Faster And Better? Because Something Is Missing. Ai Works Only When It Understands The Soul Of The Business. An Ontology Is A Holistic Digital Model Of Every Piece Of Information That Matters To The Business, From Processes To Products To People, And It's What Makes The Difference Between The Promise Of Ai And Delivering On That Promise. Business Leaders Who Want To Catch The Ai Wave--rather Than Be Crushed By It--need To Read The Ai-powered Enterprise. The Book Is The First To Combine A Sophisticated Explanation Of How Ai Works With A Practical Approach To Applying Ai To The Problems Of Business, From Customer Experience To Business Operations To Product Development. Artificial intelligence (AI) can quickly disseminate reliable information to your salespeople, enable remote repair work on machinery and even allow editors to customize newsletters to thousands of subscribers. Yet many businesses lack the organizational data infrastructure to make AI effective. Ontologies provide the necessary links among separate and distinct systems within an organization to enable enterprisewide communication. In this book, information science expert Seth Earley discusses how ontologies will help you capitalize on the advantages AI offers and be a leader in your industry In Prescriptive Analytics, analytics expert Dr. Dursun Delen illuminates the field's state-of-the-art methods, offering holistic insight for both professionals and students. Delen's end-to-end, all-inclusive approach covers optimization, simulation, multi-criteria decision-making methods, inference- and heuristic-based decisioning, and more. Balancing theory and practice, he presents intuitive conceptual illustrations, realistic example problems, and real-world case studies-all designed to deliver knowledge you can use. -- Provided by publisher This book presents an introduction to MCDA with chapters describing in detail each of the leading methods used in this field. Comparison of methods and software is also featured to enable readers to choose the most appropriate method needed in their research. Case studies are included throughout.