Informatica

In this paper we propose modifications of the well-known algorithm of particle swarm optimization (PSO). These changes affect the mapping of the motion of particles from continuous space to binary space for searching in it, which is widely used to solve the problem of feature selection. The modified binary PSO variations were tested on the dataset SVC2004 dedicated to the problem of user authentication based on dynamic features of a handwritten signature. In the example of k-nearest neighbours (kNN), experiments were carried out to find the optimal subset of features. The search for the subset was considered as a multicriteria optimization problem, taking into account the accuracy of the model and the number of features.

In the paper we propose a genetic algorithm based on insertion heuristics for the vehicle routing problem with constraints. A random insertion heuristic is used to construct initial solutions and to reconstruct the existing ones. The location where a randomly chosen node will be inserted is selected by calculating an objective function. The process of random insertion preserves stochastic characteristics of the genetic algorithm and preserves feasibility of generated individuals. The defined crossover and mutation operators incorporate random insertion heuristics, analyse individuals and select which parts should be reinserted. Additionally, the second population is used in the mutation process. The second population increases the probability that the solution, obtained in the mutation process, will survive in the first population and increase the probability to find the global optimum. The result comparison shows that the solutions, found by the proposed algorithm, are similar to the optimal solutions obtained by other genetic algorithms. However, in most cases the proposed algorithm finds the solution in a shorter time and it makes this algorithm competitive with others.

The notion of general backlash is introduced where instead of the straight lines determining the upward and downward parts of backlash characteristic general curves are considered. An analytic form of general backlash characteristic description is proposed, which is based on appropriate switching and internal functions. Consequently, this multi-valued mapping is represented by one difference equation. All the parameters in the equation describing this hard nonlinearity are separated; hence the general backlash identification can be solved as a quasi-linear problem using an iterative parameter estimation method with internal variable estimation. Also the identification of cascaded systems consisting of a general input backlash followed by a linear dynamic system is presented. Simulation studies of general backlash identification and that of cascaded systems with general input backlash are included.

The concentration of a substrate in a solution can be measured using amperometric signals of biosensors: in fact the maximum (steady state) current is measured which is calibrated in the units of concentration. Such a simple method is not applicable in the case of several substrates. In the present paper, the problem of evaluation of concentrations of several substrates is tackled by minimizing the discrepancy between the observed and modeled transition processes of the amperometric signal.

The mathematical model and methods of calculation of the layout structure of comparator signal circuits with distributed parameters are presented. The algorithm of computer formulation and solving of equations of transfer functions of comparator circuits is provided. Theoretical substantiation of optimizing the micro‐layout of large‐scale integration circuits of parallel subnanosecond analog‐to‐digital converters (ADC) is proposed.