Application of intellectual DSS to medium-term forecasting of the sea ice area in the Northern Hemisphere
The paper is devoted to the description of a new multi-purpose intellectual decision support system. We present the algorithms used and the results achieved in applying the system to analyzing and forecasting the sea ice area in the Northern Hemisphere. The impact of solar radiation on the changes in the sea ice area was confirmed. Application of interval neural nets to medium-term forecasting of sea ice area changes was justified.
Decision support in equipment condition monitoring systems with image processing is analyzed. Long-run accumulation of information about earlier made decisions is used to realize the adaptiveness of the proposed approach. It is shown that unlike conventional classification problems, the recognition of abnormalities uses training samples supplemented with reward estimates of earlier decisions and can be tackled using reinforcement learning algorithms. We consider the basic stages of contextual multi-armed bandit algorithms during which the probabilistic distributions of each state are evaluated to evaluate the current knowledge of the states, and the decision space is explored to increase the decision-making efficiency. We propose a new decision-making method, which uses the probabilistic neural network to classify abnormal situation and the softmax rule to explore the decision space. A modelling experiment in image processing was carried out to show that our approach allows a higher accuracy of abnormality detection than other known methods, especially for small-size initial training samples.
Managing Intellectual Capital and Innovation for Sustainable and Inclusive Society: Proceedings of the MakeLearn and TIIM Joint International Conference 27–29 May 2015, Bari, Italy
The article discusses the prospects of a decision support system to transport companies. The main characteristics of logistical BI-systems, proposed approaches its use to analyze the efficiency of the transport company.
An outline of a few methods in an emerging field of data analysis, “data interpretation”, is given as pertaining to medical informatics and being parts of a general interpretation issue. Specifically, the following subjects are covered: measuring correlation between categories, conceptual clustering, and generalization and interpretation of empirically derived concepts in taxonomies. It will be shown that all of these can be put as parts of the same inquiry.
This proceedings bring together contributions from researchers from academia and industry to report the latest cutting edge research made in the areas of Fuzzy Computing, Neuro Computing and hybrid Neuro-Fuzzy Computing in the paradigm of Soft Computing. The FANCCO 2015 conference explored new application areas, design novel hybrid algorithms for solving different real world application problems. After a rigorous review of the 68 submissions from all over the world, the referees panel selected 27 papers to be presented at the Conference. The accepted papers have a good, balanced mix of theory and applications. The techniques ranged from fuzzy neural networks, decision trees, spiking neural networks, self organizing feature map, support vector regression, adaptive neuro fuzzy inference system, extreme learning machine, fuzzy multi criteria decision making, machine learning, web usage mining, Takagi-Sugeno Inference system, extended Kalman filter, Goedel type logic, fuzzy formal concept analysis, biclustering etc. The applications ranged from social network analysis, twitter sentiment analysis, cross domain sentiment analysis, information security, education sector, e-learning, information management, climate studies, rainfall prediction, brain studies, bioinformatics, structural engineering, sewage water quality, movement of aerial vehicles, etc.
In modern world enterprises need to be agile in their operation and structure to react to changes quickly. One of the open questions here is how to develop the enterprise, or, to be more precise, if enterprise needs to be developed, and if yes, in which way. In this research we are focusing on the case when enterprise stakeholders understand the need of enterprise development, have ideas for that, and they need decision support method to understand if enterprise restructuring is likely to be successful and cost effective. Another covered topic is how to choose the best option for restructuring from variety provided. In this paper we describe the developed decision support method which combines DEMO methodology and transaction costs theory for quantitative costs estimation. To make this method applicable and reproducible we proposed few enhancements to DEMO notation.
In the paper an approach to identification of characteristics for assessment of IT strategic decisions is proposed. The main feature of the approach is associated with integration of Balanced Scorecard methodology for IT service (IT Balanced Scorecard) and COBIT standard. Such integration allows to describe a hierarchical structure of characteristics (metrics) for assessment of decisions efficiency in yje field of information technologies.