Search results for "decision tree"
showing 10 items of 170 documents
A methodology for fire data analysis based on pattern recognition towards the disaster management
2015
The aim of this paper is to investigate a proposed strategy for fire disaster analysis that is implemented based on pattern recognition technique in order to achieve a methodology for disaster management. Since the fire hazard has severe effects onto human and properties, it is essential to predict and possibly prevent it. Almost every fire produces some issues, such as heat, smoke, gas, and flame, which are sensible and measurable via devices or detection systems. The fire behavior is relevant to these issues. In this research, temperature, heat radiation, and visibility (smoke) data of fire that have been obtained from Fire Dynamics Simulator (FDS) are used for analysis. The location of t…
Pruning Incremental Linear Model Trees with Approximate Lookahead
2014
Incremental linear model trees with approximate lookahead are fast, but produce overly large trees. This is due to non-optimal splitting decisions boosted by a possibly unlimited number of examples obtained from a data source. To keep the processing speed high and the tree complexity low, appropriate incremental pruning techniques are needed. In this paper, we introduce a pruning technique for the class of incremental linear model trees with approximate lookahead on stationary data sources. Experimental results show that the advantage of approximate lookahead in terms of processing speed can be further improved by producing much smaller and consequently more explanatory, less memory consumi…
Expert-based versus citation-based ranking of scholarly and scientific publication channels
2016
Abstract The Finnish publication channel quality ranking system was established in 2010. The system is expert-based, where separate panels decide and update the rankings of a set of publications channels allocated to them. The aggregated rankings have a notable role in the allocation of public resources into universities. The purpose of this article is to analyze this national ranking system. The analysis is mainly based on two publicly available databases containing the publication source information and the actual national publication activity information. Using citation-based indicators and other available information with association rule mining, decision trees, and confusion matrices, …
Weighted distance-based trees for ranking data
2017
Within the framework of preference rankings, the interest can lie in finding which predictors and which interactions are able to explain the observed preference structures, because preference decisions will usually depend on the characteristics of both the judges and the objects being judged. This work proposes the use of a univariate decision tree for ranking data based on the weighted distances for complete and incomplete rankings, and considers the area under the ROC curve both for pruning and model assessment. Two real and well-known datasets, the SUSHI preference data and the University ranking data, are used to display the performance of the methodology.
Classification trees for multivariate ordinal response: an application to Student Evaluation Teaching
2016
Data from multiple items on an ordinal scale are commonly collected when qualitative variables, such as feelings, attitudes and many other behavioral and health-related variables are observed. In this paper we introduce a method to derive a distance-based tree for multivariate ordinal response that allows, when subject-specific characteristics are available, to derive common profiles for respondents giving the same/similar multivariate ratings. Special attention will be paid to the performance comparison in terms of AUC, for three different distances used as splitting criteria. Simulated data an a dataset from a Student Evaluation of Teaching survey will be used as illustrative examples. Th…
Flexible strategic planning of transport systems
2012
Abstract This paper presents a decision support methodology for long-range planning of transport systems that exhibits strategic flexibility and stochastic system parameters. Unlike one-off strategic decisions, flexible decisions should be dynamically reformulated with time. The proposed methodology is based on the construction of a tree structure of multiple interlinked tactical planning problems, each associated with a scenario in the tree, where problems under scenarios at intermediate dates incorporate in their formulation the solution of the corresponding problems associated with past (future) connected scenarios. The resulting tree structure of interconnected planning decisions become…
Voltage Security Assessment by Using PFDT and CBR Methods in Emerging Power System
2018
Abstract This paper exhibits varied methods for voltage security assessment in a restructured power system. This paper primarily lays emphasis on two methods that are Probabilistic Fuzzy Decision Tree (PFDT) and Case Based Reasoning (CBR). In PFDT, Decision Tree plays an integral role for classification of system. For further classification of power system security, an algorithm is developed to categorise the buses which trouble the security most. After classification of system, by using minimum amount of load curtailment of voltages on buses which made insecure to secure load. Optimization of load is done by curtailing reactive power from insecure buses. In CBR, old cases from database are…
Communication complexity in a 3-computer model
1996
It is proved that the probabilistic communication complexity of the identity function in a 3-computer model isO(√n).
A methodology and algorithms for an optimal identification of Tourist Local Systems
2007
In last years, despite the emphasis on the importance of tourism as a leading industry in the development of a country’s economy, there is a lack of criteria and methodologies for the identification, the promotion and the governance of Tourism Local Systems (TLS). Moreover, nowadays an important debate is more and more emerging on the sustainable tourism development which involve three interconnected aspects: environmental, socio-cultural and economic. To this end, in this paper, a rigorous mathematical model is proposed for the optimal identification and dimensioning of TLS. The model here presented consists of a two stage methodology: at first, all the factors that characterize a geograph…
Learning the structure of HMM's through grammatical inference techniques
2002
A technique is described in which all the components of a hidden Markov model are learnt from training speech data. The structure or topology of the model (i.e. the number of states and the actual transitions) is obtained by means of an error-correcting grammatical inference algorithm (ECGI). This structure is then reduced by using an appropriate state pruning criterion. The statistical parameters that are associated with the obtained topology are estimated from the same training data by means of the standard Baum-Welch algorithm. Experimental results showing the applicability of this technique to speech recognition are presented. >