Early bankruptcy prediction using ENPC

Bankruptcy prediction has long time been an active research field in finance. One of the main approaches to this issue is dealing with it as a classification problem. Among the range of instruments available, we focus our attention on the Evolutionary Nearest Neighbor Classifier (ENPC). In this work we assess the performance of the ENPC comparing it to six alternatives. The results suggest that this algorithm might be considered a good choice.Publicad

An efficient program for modeling, control and optimization of hybrid renewable-conventional energy systems

-In this paper, a generic and an efficient model for hybrid renewable-conventional electrical energy systems is presented. This simulation model is successfully validated by means of HOMER. Moreover, two control strategies for electrical power dispatch are described. Furthermore, an optimization problem is formulated and solved, using Genetic algorithm technique, for optimizing the size of system components where the overall cost of the system is minimized. Four case studies are investigated. The results show a dependence of the size of the system components on the meteorological characteristics of the area under consideration, which validate the proposed methodology

Flexible protein folding by ant colony optimization

Protein structure prediction is one of the most challenging topics in bioinformatics. As the protein structure is found to be closely related to its functions, predicting the folding structure of a protein to judge its functions is meaningful to the humanity. This chapter proposes a flexible ant colony (FAC) algorithm for solving protein folding problems (PFPs) based on the hydrophobic-polar (HP) square lattice model. Different from the previous ant algorithms for PFPs, the pheromones in the proposed algorithm are placed on the arcs connecting adjacent squares in the lattice. Such pheromone placement model is similar to the one used in the traveling salesmen problems (TSPs), where pheromones are released on the arcs connecting the cities. Moreover, the collaboration of effective heuristic and pheromone strategies greatly enhances the performance of the algorithm so that the algorithm can achieve good results without local search methods. By testing some benchmark two-dimensional hydrophobic-polar (2D-HP) protein sequences, the performance shows that the proposed algorithm is quite competitive compared with some other well-known methods for solving the same protein folding problems

Ascent trajectory optimisation for a single-stage-to-orbit vehicle with hybrid propulsion

This paper addresses the design of ascent trajectories for a hybrid-engine, high performance, unmanned, single-stage-to-orbit vehicle for payload deployment into low Earth orbit. A hybrid optimisation technique that couples a population-based, stochastic algorithm with a deterministic, gradient-based technique is used to maximize the nal vehicle mass in low Earth orbit after accounting for operational constraints on the dynamic pressure, Mach number and maximum axial and normal accelerations. The control search space is first explored by the population-based algorithm, which uses a single shooting method to evaluate the performance of candidate solutions. The resultant optimal control law and corresponding trajectory are then further refined by a direct collocation method based on finite elements in time. Two distinct operational phases, one using an air-breathing propulsion mode and the second using rocket propulsion, are considered. The presence of uncertainties in the atmospheric and vehicle aerodynamic models are considered in order to quantify their effect on the performance of the vehicle. Firstly, the deterministic optimal control law is re-integrated after introducing uncertainties into the models. The proximity of the final solutions to the target states are analysed statistically. A second analysis is then performed, aimed at determining the best performance of the vehicle when these uncertainties are included directly in the optimisation. The statistical analysis of the results obtained are summarized by an expectancy curve which represents the probable vehicle performance as a function of the uncertain system parameters. This analysis can be used during the preliminary phase of design to yield valuable insights into the robustness of the performance of the vehicle to uncertainties in the specification of its parameters

Regional Economic Policy: Structured Approach and Tools (The Oretical Formulation

The subject matter of the article is the development of a doctrine of coordinated regional development and the study of the structural quality of development of regional systems based on the theoretical analysis of institutional factors (parameters) that determine the technological efficiency of the regional economy. The purpose is to show possibilities of technological changes and the shift of economic growth in a particular regional system, with strict limits for accelerated development, with emphasis on industrial regions. For this purpose, we generated a number of structural models, analyzed the impact of technological factors on parameters of growth of the regional economy and determined conditions for development of industrial regions. We applied correlative and regression analysis to establish a statistically significant correlation between relevant parameters, used econometric models to show the possibility to estimate parameters of growth through control parameters, including technological factor. The structural aspect of regional economic growth is measured by dividing investments into two classes: old and new technologies. It is possible to increase the technological efficiency of the regional economy by improving results with regard to used (old) technologies and applying new technologies. This approach fundamentally refines the priority queue algorithm for regional development, provides a choice of a strategy of regional technological development. When resources are directed only to the latest technologies, the disproportion in development of the regional economic system can dramatically increase, and parameters related to diversion of resources and creation of a new resource will determine the growth rate of the region. The behavior of investment in old technologies has a major impact on the rate of regional economic growth in Russia, while investments in new technologies are minor and did not have an equivalent impact on the economic growth rate compared with old technologies. Institutional corrections that define parameters of resource diversion from old technologies and creation of a new resource for development, will determine the quality of new economic growth

Linking and Weighting Efficiency Estimates with Stock Performance in Banking Firms

The purpose of this paper is to contribute further evidence on bank efficiency by defining alternative measures of costs when estimating efficiency and competitive viability by linking the results of efficiency estimates to market returns of financial institutions. Given a series of functions (production costs, opportunity costs of capital with systematic risk, opportunity cost of capital with specific risk, and branch network distribution), we estimate alternative partial measures of bank efficiency with DEA. Assuming that these functions are related to market returns on shares, an estimation of the relative importance of each of the functions is carried out, considering an additional initially unknown function which can be attributed to individual differences not accounted for in the previous four definitions. Due to the nature of the model, strong collinearity may be expected among efficiency measures. With the aid of a tabu search procedure, artificial instrumental variables are generated which avoid collinearity and permit the isolation of the underlying relationships. Results are applied to all Spanish banks quoting on the stock exchange.

Flexible Transmission Network Planning Considering the Impacts of Distributed Generation

The restructuring of global power industries has introduced a number of challenges, such as conflicting planning objectives and increasing uncertainties,to transmission network planners. During the recent past, a number of distributed generation technologies also reached a stage allowing large scale implementation, which will profoundly influence the power industry, as well as the practice of transmission network expansion. In the new market environment, new approaches are needed to meet the above challenges. In this paper, a market simulation based method is employed to assess the economical attractiveness of different generation technologies, based on which future scenarios of generation expansion can be formed. A multi-objective optimization model for transmission expansion planning is then presented. A novel approach is proposed to select transmission expansion plans that are flexible given the uncertainties of generation expansion, system load and other market variables. Comprehensive case studies will be conducted to investigate the performance of our approach. In addition, the proposed method will be employed to study the impacts of distributed generation, especially on transmission expansion planning.