Types of Reaction to Frustration: An Heuristic Classification.

2007 ◽  
pp. 280-282
Author(s):  
Saul Rosenzweig
Keyword(s):  
Heuristic Classification

Geographies of transport III

2017 ◽  
Vol 42 (3) ◽  
pp. 463-472 ◽  
Author(s):  
Tim Schwanen
Keyword(s):  
Latin America ◽  
Knowledge Production ◽  
Classification Scheme ◽  
Global South ◽  
Research Practices ◽  
Heuristic Classification

This third report in the series reviews recent research on the geographies of transport in Africa, Asia and Latin America to reflect on the spatialities of knowledge production and the question as to whether a post/decolonial turn is occurring in geographical scholarship on transport. A simple and heuristic classification scheme is developed and deployed to demonstrate that predominantly western worldviews, theories, concepts, methods and research practices continue to prevail in geographical scholarship on transport in the Global South. It is also shown that this hegemony is being reworked and resisted in various ways, and the report concludes with suggestions about how geographical scholarship on transport can be worlded and ultimately decolonized further.

scholarly journals A heuristic classification of woody plants based on contrasting shade and drought strategies

2019 ◽  
Vol 39 (5) ◽  
pp. 767-781 ◽  
Author(s):  
Liang Wei ◽  
Chonggang Xu ◽  
Steven Jansen ◽  
Hang Zhou ◽  
Bradley O Christoffersen ◽  
...  
Keyword(s):  
Woody Plants ◽  
Heuristic Classification

CLASSIFICATIONS OF CREDIT CARDHOLDER BEHAVIOR BY USING FUZZY LINEAR PROGRAMMING

2004 ◽  
Vol 03 (04) ◽  
pp. 633-650 ◽  
Author(s):  
JING HE ◽  
XIANTAO LIU ◽  
YONG SHI ◽  
WEIXUAN XU ◽  
NIAN YAN
Keyword(s):  
Linear Programming ◽  
Portfolio Management ◽  
Credit Card ◽  
Real Life ◽  
Research Direction ◽  
Fuzzy Linear Programming ◽  
Research Topics ◽  
Score System ◽  
Main Research ◽  
Heuristic Classification

Behavior analysis of credit cardholders is one of the main research topics in credit card portfolio management. Usually, the cardholder's behavior, especially bankruptcy, is measured by a score of aggregate attributes that describe cardholder's spending history. In real-life practice, statistics and neural networks are the major players to calculate such a score system for prediction. Recently, various multiple linear programming-based classification methods have been promoted for analyzing credit cardholders' behaviors. As a continuation of this research direction, this paper proposes a heuristic classification method by using the fuzzy linear programming (FLP) to discover the bankruptcy patterns of credit cardholders. Instead of identifying a compromise solution for the separation of credit cardholder behaviors, this approach classifies the credit cardholder behaviors by seeking a fuzzy (satisfying) solution obtained from a fuzzy linear program. In this paper, a real-life credit database from a major US bank is used for empirical study which is compared with the results of known multiple linear programming approaches.

Towards the Unification of Inference Structures in Medical Diagnostic Tasks

1998 ◽  
Vol 37 (01) ◽  
pp. 109-118 ◽  
Author(s):  
J. Rives ◽  
A. E. Delgado ◽  
R. Martínez ◽  
J. Mira
Keyword(s):  
Therapy Planning ◽  
Clinical Environment ◽  
Medical Diagnoses ◽  
Equivalent Models ◽  
Ongoing Work ◽  
Medical Diagnostic ◽  
Generic Tasks ◽  
Heuristic Classification ◽  
Comparison Criteria ◽  
Central Purpose

Abstract:The central purpose of artificial intelligence applied to medicine is to develop models for diagnosis and therapy planning at the knowledge level, in the Newell sense, and software environments to facilitate the reduction of these models to the symbol level. The usual methodology (KADS, CommonKADS, GAMES, HELIOS, Protégé, etc.) has been to develop libraries of generic tasks and resuable problem-solving methods with explicit ontologies. The principal problem which clinicians have with these methodological developments concerns the diversity and complexity of new terms whose meaning is not sufficiently clear, precise, unambiguous and consensual for them to be accessible in the daily clinical environment. As a contribution to the solution of this problem, we develop in this article the conjecture that one inference structure is enough to describe the set of analysis tasks associated with medical diagnoses. To this end, we first propose a modification of the systematic diagnostic inference scheme to obtain an analysis generic task and then compare it with the monitoring and the heuristic classification task inference schemes using as comparison criteria the compatibility of domain roles (data structures), the similarity in the inferences, and the commonality in the set of assumptions which underlie the functionally equivalent models. The equivalences proposed are illustrated with several examples. Note that though our ongoing work aims to simplify the methodology and to increase the precision of the terms used, the proposal presented here should be viewed more in the nature of a conjecture.

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