Juan B. Grau

Compromise programming calibration for financial analysis of firms of a common sector of business, case study for a set of Spanish banks in 1995

To perform a Financial Analysis (FA) procedure on a set of different firms of the same business sector and region or stock market (maybe with a definite management goal) a set from 7 to 20 balance ratios is chosen as representative of the firms situation, and a benchmark set of good firms of the same kind is selected to calibrate the ratios as attribute variables using Compromise Programming (CP) comparison procedures. For that using the ratios of the benchmark set a reference CP ideal point is obtained, and with it for each ratio a reduced Ratio Quality Index (RQI) is obtained containing a relative CP quality evaluation. From these RQI, a CP Global Utility Index (GUI) of each firm is then proposed, using a common set of chosen CP weights to incorporate the effect of each ratio on the quality of the firms for the intended FA study, with indication of some special techniques including possible use of utility-like functions. An illustrative case study follows with normalized balance sheets data of some main Spanish banks in 1995, showing that some of the real features of this suggestive example are put in evidence by this method, that quality classification depends on various factors, and that external wide information is necessary and gets incorporated with the proposed method. A discussion follows concerning the case, the method and possible future developments.

MCDM Methods for Territorial Services Planning in an Andine Rural Area

For election of a system of disposal of urban residues in small andine cities of the Provincia de Salta, Argentina, some discrete MCDM methods were found adequate and were used choosing between three alternatives {direct filling, sanitary filling+compost and transport out of the city}, after a local team defined and elicited a comprehensive set of criteria. ELECTRE-I and PROMETHEE methods were performed, requiring elicitation of weights and some adaptations. A.H.P. was locally performed. The second alternative was preferred with the three methods.

Sustainable agriculture using an intelligent mechatronic system

The goal of the Project group created by U.P.M. in collaboration with foreign universities, research institutions and companies is the development of an intelligent mechatronic system for the use of precision and sustainable agriculture. The project as a whole includes the following components: photographing and decoding of the soil surface; fertility determination and formation of the fertility map; generation of the controlling signal for mechatronic dosing device; intelligent dosing of fertilizers; simulation, prototype and testing; human-machine interaction and training preparation.

Fractals as Pre-Processing Tool for Computational Intelligence Application

Preprocessing is the process of adapting the input of our Computational Intelligence (CI) problem to the CI technique applied. Images are inputs of many problems, and Fractal processing of the images to extract relevant geometry characteristics is a very important tool. This chapter is dedicated to Fractal Preprocessing. In Pedology, fractal models were fitted to match the structure of soils and techniques of multifractal analysis of soil images were developed as is described in a state-of-the-art panorama. A box-counting method and a gliding box method are presented, both obtaining from images sets of dimension parameters, and are evaluated in a discussed case study from images of samples, and the second seems preferable. Finally, a comprehensive list of references is given

Application of ELECTRE I Method to Restoration Actions in Telecommunication Network Maintenance

Maintenance of a telecommunication network is a complex problem. Equipments and links suffer incidences everyday that have to be solved to assure the customers quality of service. But the resources that a company have to solve its network problems, are limited. It is necessary to take correct decisions about maintenance actions. The success of incidences resolution depends on this. In this work, we study the application of discrete multicriteria decision-making methods [1] to this problem. Specifically, we explain how ELECTRE I method [2] can be used in an effective manner, obtaining practical results.

Scaling Characteristics of Soil Structure

As previously discussed in Chap. 5, soil structure is defined by the spatial arrangement of soil primary particles and aggregates. There is increasing evidence that quantitative characterization of the soil structure and of its heterogeneity and complexity holds the key to a deeper understanding on physical, chemical, and biological processes that take place within them (Vogel 2000; Rockhold et al. 2004; Young et al. 2008; Blair et al. 2007; Pajor et al. 2010; Kravchenko et al. 2010; Dullien 2012).Therefore, it is very important to obtain an accurate description of it which best approximates to reality. Although many parameters may be used to attempt to describe irregular morphology, the spatial arrangement of the most prominent features is a challenging problem across a wide range of disciplines (Ripley 1988; Griffith 1988; Baveye and Boast 1988).

Mathematical Models to Elaborate Plans for Adaptation of Rural Communities to Climate Change

Climate change is on the policy agenda at the global level, with the aim of understanding and reducing its causes and to mitigate its consequences. In most countries and international organizations, the efforts and debates have been directed to know the possible causes, to predict the future evolution of some variable conditioners, trying to make studies to fight against the effects or to delay its negative evolution. This article presents the results from a global model that can help to choose the best alternative among the feasible ones, by taking into consideration environment and population as the main criteria.

Mathematical decision theory applied to land capability: a case study in the community of madrid.

In land evaluation science, a standard data set is obtained for each land unit to determine the land capability class for various uses, such as different farming systems, forestry, or the conservation or suitability of a specific crop. In this study, we used mathematical decision theory (MDT) methods to address this task. Mathematical decision theory has been used in areas such as management, finance, industrial design, rural development, the environment, and projects for future welfare to study quality and aptness problems using several criteria. We also review MDT applications in soil science and discuss the suitability of MDT methods for dealing simultaneously with a number of problems. The aim of the work was to show how MDT can be used to obtain a valid land quality index and to compare this with a traditional land capability method. Therefore, an additive classification method was applied to obtain a land quality index for 122 land units that were compiled for a case study of the Community of Madrid, Spain, and the results were compared with a previously assigned land capability class using traditional methods based on the minimum requirements for land attributes.

Application of Decision Theory methods for a soil classification in the Community of Madrid (Spain)

A land classification method was designed for the Community of Madrid (CM), which has lands suitable for either agriculture use or natural spaces. The process started from an extensive previous CM study that contains sets of land attributes with data for 122 types and a minimum-requirements method providing a land quality classification (SQ) for each land. Borrowing some tools from Operations Research (OR) and from Decision Science, that SQ has been complemented by an additive valuation method that involves a more restricted set of 13 representative attributes analysed using Attribute Valuation Functions to obtain a quality index, QI, and by an original composite method that uses a fuzzy set procedure to obtain a combined quality index, CQI, that contains relevant information from both the SQ and the QI methods.

Comparison of Brans Promethee multicriteria decision method and Promethee modified by authors for the optimization of an erosion control integral plan in Chaco area in Salta province (Argentine)

Chaco area is situated in the Province of Salta at North West of Argentine. The desertification is a big problem. In order to mitigate the problem it is necessary to take into account not only pedologic criteria but the economical, environmental, cultural and sociological criteria. Six sub zones have been established following previous studies. Eight criteria and six alternatives have been introduced in the model. Following the results of the study carried out by a collaborative project between UPM and UCS financed by AECID (1) were established several initial matrix. Brans Promethee Multicriteria Decision Method (MCDM) was applied and the authors modified that method introducing weights like in Electre Method.