Coevolutionary Approach to Extracting and Predicting Linked Sets of Complex Decision Rules from Activity Diary Data

2001 ◽  
Vol 1752 (1) ◽  
pp. 126-132 ◽  
Author(s):  
Theo Arentze ◽  
Harry Timmermans
Keyword(s):  
Decision Rules ◽  
Diary Data ◽  
Complex Decision ◽  
Activity Diary

Reinduction of Albatross Decision Rules with Pooled Activity-Travel Diary Data and an Extended Set of Land Use and Cost-Related Condition States

2003 ◽  
Vol 1831 (1) ◽  
pp. 230-239 ◽  
Author(s):  
Theo Arentze ◽  
Frank Hofman ◽  
Harry Timmermans
Keyword(s):  
Process Model ◽  
Goodness Of Fit ◽  
Decision Rules ◽  
Data Sets ◽  
Related Condition ◽  
Diary Data ◽  
Travel Diary ◽  
Complete Set ◽  
Individual Decisions ◽  
Activity Diary

Operationalization of the Albatross model—a rule-based model of activity-travel scheduling—is described for applications on a national scale. For this purpose, the original model was extended to include the generation of schedule skeletons and travel cost variables. Furthermore, to account for the increase of scale of the study area, the location decision component of the model was completely restructured. The complete set of 27 decision trees involved in the decision process model were newly induced from several pooled existing activity diary data sets in the Netherlands. The results indicate that the goodness of fit of the model is satisfactory at the level of individual decisions as well as aggregate distributions.

Exploratory data analysis of activity diary data: a space–time GIS approach

2011 ◽  
Vol 19 (3) ◽  
pp. 394-404 ◽  
Author(s):  
Jie Chen ◽  
Shih-Lung Shaw ◽  
Hongbo Yu ◽  
Feng Lu ◽  
Yanwei Chai ◽  
...  
Keyword(s):  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Space Time ◽  
Diary Data ◽  
Exploratory Data ◽  
Activity Diary

scholarly journals Ant-based extraction of rules in simple decision systems over ontological graphs

2015 ◽  
Vol 25 (2) ◽  
pp. 377-387 ◽  
Author(s):  
Krzysztof Pancerz ◽  
Arkadiusz Lewicki ◽  
Ryszard Tadeusiewicz
Keyword(s):  
Rough Set ◽  
Heuristic Algorithm ◽  
Decision Rules ◽  
Decision Systems ◽  
Dominance Principle ◽  
Clustering Approach ◽  
Complex Decision ◽  
Semantic Spaces

Abstract In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominancebased rough set approach (DRSA). In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems

scholarly journals Case studies for precision agriculture

2017 ◽  
Vol 38 (SI 2 - 6th Conf EFPP 2002) ◽  
pp. 704-710
Author(s):  
J. Šilha ◽  
P. Hamouz ◽  
V. Táborský ◽  
K. Štípek ◽  
J. Šnobl ◽  
...  
Keyword(s):  
Soil Ph ◽  
Precision Agriculture ◽  
Crop Production ◽  
Crop Protection ◽  
Decision Rules ◽  
Available P ◽  
Agrochemical Properties ◽  
P Content ◽  
Complex Decision ◽  
Soil Agrochemical Properties

The results of spatial variability of plant-available soil nutrients (P, K, Mg) and soil pH are described in this paper. Experiment was realized on the field of area 72 ha (orthic luvisol), located in the area of Český Brod. The use of coefficient of variation as a criterion of variability of soil agrochemical properties and yield on the field showed the following: the highest variability was observed in available P, the second highest variability was in available K, and the lowest variability of main non-mobile nutrients was in the available Mg. Soil pH was the lowest of all measured soil properties. Although the highest correlation coefficient between the soil available P content and soil pH was established, the process of spatial dependence was not detected. Detailed field scouting and others data can be important elements, as can complex decision rules, taking into account additional factors such as the characteristics of crop protection agents and preferences of the farm manager. This paper illustrates, how to plant nutritions, crop protection, crop production might be integrated to support these diseases and weeds management decisions.

How complex decision rules can impede behavior adherence

2007 ◽  
Author(s):  
Jutta Mata ◽  
Peter M. Todd ◽  
Sonia Lippke
Keyword(s):  
Decision Rules ◽  
Complex Decision
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