| A Close Shave With Occams Razor |
AR-PA-001 |
Earl Cox demonstrates the value of fuzzy logic as a business tool with three contemporary examples - Substance Abuse Treatment, Mergers and Acquisitions Analysis, and New Product Pricing.
Vol 13 - Issue 3 (May/June 1999) READ MORE > |
| What Does Your Company Do |
AR-PA-002 |
Earl Cox points out how machine learning technologies provide the core understanding of how a business process actually works.
Vol 13 - Issue 4 (July/August 1999) READ MORE > |
| Fuzzy Knowledge Bases |
AR-PA-003 |
| Earl Cox describes Fuzzy Knowledge Bases, combining both the semantics of information with the imprecision found in nearly all real-world problems. READ MORE > |
| Genetically Tuned Fuzzy Models |
AR-PA-004 |
Earl Cox explores ways to make your models more responsive to change in demographics and the economy.
Vol 13 - Issue 5 (September/October 1999) READ MORE > |
| A Project Risk Assessment Model |
AR-PA-005 |
Earl Cox explores a system that analyzes and then predicts the risk inherent in a project.
Vol 13 - Issue 6 (November/December 1999) READ MORE > |
| Distributed Intelligence in B2B Universe |
AR-PA-006 |
Earl Cox illustrates how two crucial types of computational intelligence models, fuzzy and neural systems, fit into the emerging distributed data mart architectures forming the core knowledge repositories for companies doing business across the Internet.
Vol 14 - Issue 3 (May/June 2000) READ MORE > |
| Hybrid Text Mining |
AR-PA-007 |
Earl Cox describes the application of a hybrid approach to finding hidden relationships within large databases revealing deep insight and generating significant financial and commercial results.
Vol 14 - Issue 5 (September/October 2000) READ MORE > |
| Fuzzy SQL |
AR-PA-008 |
Earl Cox illustrates how the use of fuzzy logic in database queries can improve over-all accuracy by returning records that match the intent instead of the mathematics of the query. Fuzzy queries also return a set of records ranked according to their proximity to the query intent.
Vol 14 Issue 1 (Jan/Feb 2000) READ MORE > |
| XML and Distributed B2B Intelligence |
AR-PA-009 |
Earl Cox explores the new relationship between applications and intelligence and how combining business policy rules and XML capabilities provides a powerful, robust and extensible way of building distributed applications.
Vol 15 - Issue 2 (March/April 2001) READ MORE > |
| Fuzzy Logic in eCommerce Experts Systems |
AR-PA-010 |
Earl Cox examines the ways in which quantitative and qualitative uncertainties are used to make decisions in modern, high-speed, high-volume eCommerce systems.
Vol 15 - Issue 3 (May/June 2001) READ MORE > |
| Knowledge Navigator |
AR-PA-011 |
Earl Cox examines a knowledge management system, incorporating an expertise repository and adaptive feedback to rate of the expert's knowledge and abilities, thus bridging the gap between those with knowledge and those in need.
Vol 15 - Issue 4 (July/August 2001) READ MORE >
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| Building Intelligent Models |
AR-PA-012 |
Earl Cox explores key issues associated with knowledge-based model design and execution including data variables, data and fuzzy spaces, experimental controls, coping with noise, ambiguity, missing data, isolation of dependent and independent variables, and statistical and regression analyses.
Vol 15 Issue 5 (September/October 2001) READ MORE > |
| CI and Threat Assessment |
AR-PA-013 |
| Earl Cox examines how advanced artificial intelligence technologies will become crucial to the traditional intelligence service in the fight against terrorism. Vol 15 Issue 6 (November/December 2001) READ MORE > |
| Object and Knowledge Based Modeling |
AR-PA-014 |
Earl Cox examines the object revolution and shows how it has changed the face of expert systems given the resurgence in business intelligence systems and predictive data mining and the resulting relationship between object representation and rule-based expert systems.
Volume 16 Issue 2 (March/April 2002) READ MORE > |
| Seeing the Invisible |
AR-PA-015 |
| Earl Cox explores the ways in which computational intelligence and, in particular, Fuzzy Logic can be used to isolate and quantify behavior patterns buried deep in the masses of often noisy data. Volume 16 Issue 1 (Jan/Feb 2002) READ MORE > |
| A Protocycling Methodology |
AR-PA-016 |
Earl Cox examines a prototyping methodology for organizing and building intelligent rule-based business models and how the methodology directs the evolution, development, and deployment of business models.
Volume 16 Issue 3 (May/June 2002) READ MORE > |
