Izbor metode za predviđanje ekonomskih rezultata tvrtki

This paper reports on the efforts to find a method for predicting economic results of companies. The input data files consist of 93 profitable companies and 93 bankrupt firms. From the total number of 93 firms in both categories, data of 72 firms served for establishing a classification criterion, and for the rest of 21 firms, a prognosis of their economic development was performed. The classification criterion for prognosticating the future economic development has been established by applications of discriminate analysis, logit analysis, and artificial neural network methods. The application of artificial neural networks has provided for better classification accuracies of 90,48 % for successful firms, and 100 % for bankrupt firms.U ovom se članku opisuju pokušaji pronalaska učinkovite metode za predviđanje ekonomskog rezultata tvrtki. Datoteke ulaznih podataka sastoje se od 93 uspješne tvrtke i 93 tvrtke koje su bankrotirale. Od ukupnog broja od 93 tvrtke u obje kategorije datoteka s ulaznim podacima, podaci za 72 tvrtke poslužili su za određivanje klasifikacijskog kriterija a za preostalu 21 tvrtku provela se prognoza njihovog ekonomskog razvoja. Klasifikacijski kriterij za predviđanje budućeg ekonomskog razvoja tvrtke uspostavljen je primjenom analize diskriminacije, logičkom regresijom i metodama umjetne neuronske mreže. Primjena logičke regresije i umjetnih neuronskih mreža omogućila je bolju klasifikacijsku točnost u slučaju 90,48 % uspješnih tvrtki i 100 % tvrtki koje su bankrotirale

An Efficient Local Search for Partial Latin Square Extension Problem

A partial Latin square (PLS) is a partial assignment of n symbols to an nxn grid such that, in each row and in each column, each symbol appears at most once. The partial Latin square extension problem is an NP-hard problem that asks for a largest extension of a given PLS. In this paper we propose an efficient local search for this problem. We focus on the local search such that the neighborhood is defined by (p,q)-swap, i.e., removing exactly p symbols and then assigning symbols to at most q empty cells. For p in {1,2,3}, our neighborhood search algorithm finds an improved solution or concludes that no such solution exists in O(n^{p+1}) time. We also propose a novel swap operation, Trellis-swap, which is a generalization of (1,q)-swap and (2,q)-swap. Our Trellis-neighborhood search algorithm takes O(n^{3.5}) time to do the same thing. Using these neighborhood search algorithms, we design a prototype iterated local search algorithm and show its effectiveness in comparison with state-of-the-art optimization solvers such as IBM ILOG CPLEX and LocalSolver.Comment: 17 pages, 2 figure

Strength in numbers:combining multi-source remotely sensed data to model plant invasions in coastal dune ecosystems

International audienceA common feature of most theories of invasion ecology is that the extent and intensity of invasions is driven by a combination of drivers, which can be grouped into three main factors propagule pressure (P), abiotic drivers (A) and biotic interactions (B). However, teasing apart the relative contribution of P, A and B on Invasive Alien Species (IAS) distributions is typically hampered by a lack of data. We focused on Mediterranean coastal dunes as a model system to test the ability of a combination of multi-source Remote Sensing (RS) data to characterize the distribution of five IAS. Using generalized linear models, we explored and ranked correlates of P, A and B derived from high-resolution optical imagery and three-dimensional (3D) topographic models obtained from LiDAR, along two coastal systems in Central Italy (Lazio and Molise Regions). Predictors from all three factors contributed significantly to explaining the presence of IAS, but their relative importance varied among the two Regions, supporting previous studies suggesting that invasion is a context-dependent process. The use of RS data allowed us to characterize the distribution of IAS across broad, regional scales and to identify coastal sectors that are most likely to be invaded in the future. © 2019 by the authors

Interactively solving school timetabling problems using extensions of constraint programming

Timetabling problems have been frequently studied due to their wide range of applications. However, they are often solved manually because of the lack of appropriate computer tools. Although many approaches mainly based on local search or constraint programming seem to have been quite successful in recent years, they are often highly dedicated to specific problems and encounter difficulties to take the dynamic and over-constrained nature of such problems. We were confronted with such an over-constrained and dynamic problem in our institution. This paper deals with a timetabling system based on constraint programming with the use of explanations to offer a dynamic behaviour and to allow automatic relaxations of constraints. Our tool has successfully answered the needs of the current planner by providing solutions in a few minutes instead of a week of manual design.We present in this paper the techniques used, the results obtained and a discussion on the effects of the automation of the timetabling process

Constraint Solving on Bounded String Variables

Abstract Constraints on strings of unknown length occur in a wide variety of real-world problems, such as test case generation, program analysis, model checking, and web security. We describe a set of con-straints sufficient to model many standard benchmark problems from these fields. For strings of an unknown length bounded by an integer, we describe propagators for these constraints. Finally, we provide an experi-mental comparison between a state-of-the-art dedicated string solver, CP approaches utilising fixed-length string solving, and our implementation extending an off-the-shelf CP solver.

Complete genes may pass from food to human blood

Our bloodstream is considered to be an environment well separated from the outside world and the digestive tract. According to the standard paradigm large macromolecules consumed with food cannot pass directly to the circulatory system. During digestion proteins and DNA are thought to be degraded into small constituents, amino acids and nucleic acids, respectively, and then absorbed by a complex active process and distributed to various parts of the body through the circulation system. Here, based on the analysis of over 1000 human samples from four independent studies, we report evidence that meal-derived DNA fragments which are large enough to carry complete genes can avoid degradation and through an unknown mechanism enter the human circulation system. In one of the blood samples the relative concentration of plant DNA is higher than the human DNA. The plant DNA concentration shows a surprisingly precise log-normal distribution in the plasma samples while non-plasma (cord blood) control sample was found to be free of plant DNA

COMBINATORICS IN LOGIC PROGRAMMING: IMPLEMENTATIONS AND APPLICATIONS

This paper presents a new intelligent computing approach for combinatorics problems by incorporating logic programming. Permutations, one of the most common and basic topics in combinatorics, appear in many problems in science, engineering, and business. Applications of permutations and other combinatorics problems are briefly reviewed. Implementation of permutations is presented in Prolog, the standard language of logic programming. Time complexity analysis and experimental results of running the program are also discussed. The program is optimal in terms of the order of its complexity. Applications of the technique to various domains as well as to specific problems such as the traveling salesman are discussed