Working paper
Ambiguity, Efficieny and Bank Bailouts
This abstract offers a method for ranking alternatives in a decison making problem. It determines importance of the criteria with help of factor analysis. Though the alternatives are evaluated by each of the criteria by a group of experts, the weights for the criteria are to be found with the help of factor analysis.
The algorithm of the method is as follows:
1. Under the constraint that the problem handles several evaluation criteria, several items to compare (alternatives) and several experts to give their evaluation.
2. Find the principal components that replace the input criteria implicitly.
3. To find the final mark for each of the alternatives the marks given by experts are multiplied with the regression coefficients, found in the step 2.
4. The final marks are represented in axes „crieria“ and „mark“ so that each alternative is described with a curve (trajectory). These curves represent the map of graded alternatives. Depending on the problem to be solved (min or max,) a record for each main criteria is to be found.
5. With help of special deviation measure procedures (Minkowski, Chebyshev e.t.s) a matrix of deviations from ideal solution is to be built.
6. The alternatives are to be rated in accordance to the deviation from the ideal trajectory.
To prove the effectiveness of the method it was applied to a problem for 5 alternatives, 3 experts and 38 evaluation criteria. The problem was also solved with the help of most popular method of Weighted Sum Model (WSM) and TOPSIS method. The problem was also being solved by finding the geometric mean for each alternative. The results for approaches were compared and the method, offered in this abstrat, proved itself as a feasible one.
The paper presents the results of empirical research enterpreniur decision making process. The features of modern Russian entrepreneurship, decision-making process, psychological characteristics required for different types of decision-making in organizations is identified.
Soft Computing (SC) is a consortium of fuzzy logic (FL), neurocomputing (NC), evolutionary computing (EC), probabilistic computing (PC), chaotic computing (CC) and parts of machine learning theory (ML). SC is the foundation for computational intelligence and is leading to the development of numerous hybrid intelligent information, control and decision-making systems. The methodology of computing with words (CW) is an important event in the evolution of cognitive science, natural language processing, artificial intelligence, and different existing scientific theories. This is because CW can enrich the existing scientific theories and the above-mentioned science fields giving them the capability of using natural languages to operate on perception-based information, not only measurement-based information. Indeed in many real-world problems in natural sciences as well as in industrial engineering, economics, and business, often there is a need to deal with both perception and measurement based information. In the case of perception based information, the available information is not precise enough to justify the use of numbers. Such information is usually described in natural languages rather than in strict (idealized) mathematical expressions. So a strong need has appeared for a new approach, theory and technology for the development of knowledge representation, computing, and reasoning tools that allow creation of systems with high MIQ. The sessions of the ICSCCW-2011 will focus on the development and application of Soft Computing technology and computing with words paradigm in system analysis, decision and control.
Uncertainty is a concept associated with data acquisition and analysis, usually appearing in the form of noise or measure error, often due to some technological constraint. In supervised learning, uncertainty affects classification accuracy and yields low quality solutions. For this reason, it is essential to develop machine learning algorithms able to handle efficiently data with imprecision. In this paper we study this problem from a robust optimization perspective. We consider a supervised learning algorithm based on generalized eigenvalues and we provide a robust counterpart formulation and solution in case of ellipsoidal uncertainty sets. We demonstrate the performance of the proposed robust scheme on artificial and benchmark datasets from University of California Irvine (UCI) machine learning repository and we compare results against a robust implementation of Support Vector Machines.
The Seventh International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control aims at the development of Soft Computing and its Application is the Seventh of its kind. These fields have built upon mainly Fuzzy Logic originally introduced by L. Zadeh. Soft Computing (SC) is a consortium of fuzzy logic (FL), neurocomputing (NC), evolutionary computing (EC), probabilistic computing (PC), chaotic computing (CC) and parts of machine learning theory (ML). SC is the foundation for computational intelligence and is leading to the development of numerous hybrid intelligent information, control and decision making systems. The methodology of computing with words (CW) is an important event in the evolution of cognitive science, natural language processing, artificial intelligence, and different existing scientific theories. This is because CW can enrich the existing scientific theories and the above-mentioned science fields giving them the capability of using natural languages to operate on perception-based information, not only measurement-based information. Indeed, in many real-world problems in natural sciences as well as in industrial engineering, economics, and business, often there is a need to deal with both perception and measurement based information. In the case of perception based information, the available information is not precise enough to justify the use of numbers. Such information is usually described in natural languages or by means of visual images rather than in strict (idealized) mathematical expressions.So a strong need has appeared for a new approach, theory and technology for the development of knowledge representation, computing, and reasoning tools that allow creation of systems with high MIQ. The sessions of the ICSCCW-2013 will focus on the development and application of Soft Computing technology and computing with words paradigm in system analysis, decision and control.
This book constitutes the thoroughly refereed proceedings of the Third International Conference on Belief Functions, BELIEF 2014, held in Oxford, UK, in September 2014. The 47 revised full papers presented in this book were carefully selected and reviewed from 56 submissions. The papers are organized in topical sections on belief combination; machine learning; applications; theory; networks; information fusion; data association; and geometry.
Smoking is a problem, bringing signifi cant social and economic costs to Russiansociety. However, ratifi cation of the World health organization Framework conventionon tobacco control makes it possible to improve Russian legislation accordingto the international standards. So, I describe some measures that should be taken bythe Russian authorities in the nearest future, and I examine their effi ciency. By studyingthe international evidence I analyze the impact of the smoke-free areas, advertisementand sponsorship bans, tax increases, etc. on the prevalence of smoking, cigaretteconsumption and some other indicators. I also investigate the obstacles confrontingthe Russian authorities when they introduce new policy measures and the public attitudetowards these measures. I conclude that there is a number of easy-to-implementanti-smoking activities that need no fi nancial resources but only a political will.
One of the most important indicators of company's success is the increase of its value. The article investigates traditional methods of company's value assessment and the evidence that the application of these methods is incorrect in the new stage of economy. So it is necessary to create a new method of valuation based on the new main sources of company's success that is its intellectual capital.