Krystian Łapa

Częstochowa University of Technology

In this paper, a new mechanism for detecting population stagnation based on the analysis of the local improvement of the evaluation function and the infinite impulse response filter is proposed. The purpose of this mechanism is to improve the population stagnation detection capability for various optimization scenarios, and thus to improve multi-po...

In this paper, the possibilities of improving the performance of multi-population-based algorithms were tested. In the proposed approach, it was decided to test various methods and parameters of the population re-initialization mechanism, aimed at improving the diversity of individuals and preventing premature convergence, which is associated with...

Metaheuristic methods are designed to solve continuous and discrete problems. Such methods include population based algorithms (PBAs). They are distinguished by the flexibility of defining the fitness function, therefore they are a good alternative to gradient methods. However, creating new variants of PBAs that work similarly and differ in detail...

Optimising the discrete convolution operations is important due to the fast growing interest and successful applications of deep learning to various fields and industries. In response to that, we propose an algorithm that views the 2D convolution operation between matrices as a matrix multiplication that involves a Toeplitz matrix; our algorithm is...

Population Based Algorithms (PBAs) are excellent search tools that allow searching space of parameters defined by problems under consideration. They are especially useful when it is difficult to define a differentiable evaluation criterion. This applies, for example, to problems that are a combination of continuous and discrete (combinatorial) prob...

In this paper, a new nature-inspired hybrid population-based algorithm is proposed. Firstly, during its operation, it changes the size of the population to reduce the number of processed individuals. For this purpose, dedicated functions that determine the size of population for each algorithm step are used. Secondly, for each individual of the pop...

This paper deals with the problem of selecting the population size for the population-based algorithm with dynamic selection of operators (OPn). This research was undertaken to check how population size changes affect the optimization of problems in which both the parameters of the solution and its structure should be selected. Moreover, variants i...

This paper presents a method based on a population in which the parameters of individuals can be processed by operators from various population-based algorithms. The mechanism of selecting operators is based on the introduction of an additional binary parameters vector located in each individual, on the basis of which it is decided which operators...

Meta-heuristic algorithms are reliable tools for modern optimization. Yet their amount is so immense that it is hard to pick just one to solve a specific problem. Therefore many researchers hold on known, approved algorithms. But is it always beneficial? In this paper, we use the meta-heuristics for the design of cascade PID controllers and compare...

In this paper, we propose a new population-based evolutionary algorithm that automatically configures the used search mechanism during its operation, which consists in choosing for each individual of the population a single evolutionary operator from the pool. The pool of operators comes from various evolutionary algorithms. With this idea, a flexi...

The on-line signature is a biometric attribute which can be used for identity verification. It is a very useful characteristic because it is commonly accepted in societies across the world. However, the verification process using this particular biometric feature is a rather difficult one. Researchers working on identity verification involving the...

The solutions proposed in this article are based on our experience with fuzzy systems (FSs), their interpretability, and population-based algorithms (PBAs). They provide a consistent approach to the design of interpretable FSs. First, PBAs can make a useful tool for selecting both parameters and the FS structure. In practice, such structure is usua...

In the paper, fuzzy recommender systems are proposed based on the novel method for nominal attribute coding. Several flexibility parameters - subjects to learning - are incorporated to their construction, allowing systems to better represent patterns encoded in data. The learning process does not affect the initial interpretable form of fuzzy recom...

Artificial intelligence methods are used in many fields of applications. One of them is biometrics. It deals with a broadly understood analysis of physical and behavioural biometric characteristics. Behavioral characteristics are particularly important from a practical point of view. They describe, among others, learned behaviors of human beings. T...

In this paper, we propose a new population-based algorithm (PBA) that adjusts its search mechanism to the problem which is to be optimized. It uses a set of search operators used in commonly-used PBAs and this selection can be made freely. The proposed algorithm selects two operators from this set, i.e. one for exploration and the other for exploit...

This paper presents a novel approach to the design of explainable recommender systems. It is based on the Wang–Mendel algorithm of fuzzy rule generation. A method for the learning and reduction of the fuzzy recommender is proposed along with feature encoding. Three criteria, including the Akaike information criterion, are used for evaluating an opt...

In this paper, a method for optimizing the parameters of multi-objective population-based algorithms is proposed. It is based on a meta-optimization, in which an external algorithm optimizes the parameters of the main algorithm. The purpose of proposed optimization is to select the functions, on the basis of which the values of parameters of the ma...

This paper presents an application of the Zero-Order Takagi-Sugeno-Kang method to explainable recommender systems. The method is based on the Wang-Mendel and the Nozaki-Ishibuchi-Tanaka techniques for the generation of fuzzy rules, and it is best suited to predict users’ ratings. The model can be optimized using the Grey Wolf Optimizer without affe...

Verification of a signature on the basis of its dynamics is an important issue of biometrics. This kind signature is called the dynamic signature. It can be represented, among others, by the set of features determined on the basis of time characteristics: pen velocity, pen pressure on the surface of a graphics tablet, etc. Values of the features ca...

Population-based algorithms are used to solve optimization problems. In order to improve their efficiency, new ways of processing the population are investigated. One approach is to use many populations which operations are synchronized with each other. In this article, we propose a new approach in which specified populations are processed using di...

Genetic programming algorithms and other population-based methods are a convenient tool for solving complex interdisciplinary problems. Their characteristic feature is that they flexibly adapt to the problem and expectations of a designer. In this paper, they are used for designing complex control systems. In particular, a new approach for automati...

The purpose of instance selection is to reduce the data size while preserving as much useful information stored in the data as possible and detecting and removing the erroneous and redundant information. In this work, we analyze instance selection in regression tasks and apply the NSGA-II multi-objective evolutionary algorithm to direct the search...

The controllers are interesting type of information systems. Their structure and parameters for atypical applications usually are selected by trial and error method, which can be time-consuming. In this paper a controller structure, which is an ensemble of PID controller and fuzzy system, and an automatic evolutionary method for its construction is...

In this paper a new population-based algorithm for nonlinear modeling is proposed. Its advantage is the automatic selection of evolutionary operators and their parameters for individuals in population. In this approach evolutionary operators are selected from a large set of operators, however only the solutions that use low number of operators are...

This paper presents original solutions from the field of intelligent expert systems for use in behavioral biometrics. They combine possibilities offered by biometric methods with the theory of fuzzy sets and the theory of population-based algorithms. Behavioral biometrics is concerned with learned behaviors such as a way of signing, movement, speak...

In this paper a new approach for automatic design of PID controllers is presented. It is based on meta-heuristic hybrid algorithm which is a combination of the genetic algorithm and the imperialist one. Main characteristic of the proposed approach is capability to design the structure and the structure parameters of a controller. It is a big advant...

Fuzzy systems are well suited for nonlinear modeling. They can be effectively used if their structure and structure parameters are properly chosen. Moreover, it should be ensured that system rules are clear and interpretable. In this paper we propose a new algorithm for automatic learning and new interpretability criteria of fuzzy systems. Interpre...

In this paper a new approach to fuzzy controller construction which combines features of proportional-integralderivative controllers and flexible fuzzy systems is proposed. Flexibility of the fuzzy systems used makes it possible to interpret a control process and reduce the controller structure, which can make hardware implementation easier. The pr...

In this paper a weighted fuzzy genetic programming algorithm for selection of structure and parameters of fuzzy systems for nonlinear modelling is proposed. This method is based on fuzzy genetic programming and innovations in this method concern, among the others, using weights of fuzzy aggregation operators, using weights of fuzzy rules, using fit...

In this paper a new algorithm for online management of fuzzy rules base for nonlinear modeling is proposed. The online management problem is complex due to limitations of memory and time needed for calculations. The proposed algorithm allows an online creation and management of fuzzy rules base. It is distinguished, among the others, by mechanisms...

In this paper a new method for elastic H ∞ -optimal fractional order PID with FIR filters (FOPID+FIR) controller design using hybrid population-based algorithm is presented. With the use of a population-based algorithm an initial structure of the controller is adjusted in a such way that the designed controller fulfills the control objective in the...

Population-based algorithms are an interesting tool for solving optimization problems. Their performance depends not only on their specification but also on methods used for initialization of initial population. In this paper a new hybridization approach of initialization methods is proposed. It is based on classification of initialization methods...

Dynamic signature can be represented by a set of global features. These features are interpreted as e.g. number of pen ups, time of signing process, etc. Values of global features can be determined on the basis of non-linear waveforms defining dynamics of the signature. They are acquired using graphic tablet or a device with a touch screen. In this...

In this paper a new method based on a population-based algorithm with flexible selectable operators for nonlinear modeling is proposed. This method enables usage of any types of exploration and exploitation operators, typical for population-based algorithms. Moreover, in proposed approach each solution from population encodes activity and parameter...

In this paper a new structure of fuzzy PID controllers with FIR filters and a method for selecting its parameters is presented. The proposed solution can be particularly important in solving problems with noise of the object’s feedback signals. To confirm the effectiveness of the proposed method a typical control problem was tested.

In this paper we proposed a new approach for interpretability of the neuro-fuzzy systems. It is based on appropriate use of parametric triangular norms with weights of arguments, which shape depends on values of their parameters and weights. The use of those norms as aggregation and inference operators increases precision of fuzzy system. Due to th...

In this paper a new method for fuzzy nonlinear modeling is proposed. This method is a hybridization of genetic algorithm and genetic programming. The innovations in this method concern, among others, using weights of aggregation operators, fitness function criteria and possibilities of automatic creation of fuzzy rules base. The proposed method was...

In this paper we propose a new approach for nonlinear modelling. It uses capabilities of the Takagi-Sugeno neuro-fuzzy systems and population based algorithms. The aim of our method is to ensure that created model achieves appropriate accuracy and is as compact as possible. In order to obtain this aim we incorporate semantic information about creat...

In the paper a method for the design of the control system is presented. With the use of an evolutionary methods an initial structure of the controller is adjusted such that the designed controller fulfills the control objective in the best way possible. This elastic structure consists of basic functional blocks and filters. The proposed method is...

The problem of online nonlinear modelling emerges among others from limitations of memory. This problem is often solved by using evolving systems. Evolving fuzzy systems play significant role as they are distinguishable by clear representation of knowledge (by fuzzy rules) which allows an interpretation of their behavior. The structure and the para...

In this paper a new approach for designing control systems is presented. It is based on ensemble of PID controller and flexible neuro-fuzzy system with dynamic structure. A hybrid population-based algorithm is proposed to select the structure and its parameters. In this hybridization a genetic algorithm is used to select the controller structure an...

In this paper a new approach for automatic design of control systems is presented. Typical control system design is difficult and time consuming. The approach proposed in this paper allows to automate this process by means of hybrid genetic-fruit fly algorithm. Genetic algorithm is used for controller structure selection, while fruit fly algorithm...

An approach proposed in this paper allows to select neuro-fuzzy classifiers taking into account new interpretability criteria. Those criteria are focused not only on complexity of the system, but also on semantics of the rules. The approach uses capabilities of new hybrid population algorithm which is a combination of the genetic algorithm and the...

An approach proposed in this paper uses a new hybrid population-based algorithm. This algorithm is a fusion between genetic algorithm and firework algorithm. Proposed approach aims on solving complex optimization problems in which not only structure parameters of the solution have to be selected, but also the mentioned structure. Proposed approach...

In this paper a new approach to automatic design of controllers is proposed. It is based on a knowledge about modelling object and capabilities of the genetic programming. In particular, a new type of the problem encoding, new evolutionary operators (tuning operator and mutation operator) and new initialization method are proposed. Moreover, a modi...

In this paper a new approach for construction of neuro-fuzzy systems for nonlinear classification is introduced. In particular, we concentrate on the flexible neuro-fuzzy systems which allow us to extend notation of rules with weights of fuzzy sets. The proposed approach uses possibilities of hybrid evolutionary algorithm and interpretability crite...

In this paper a new approach for automatic design of control systems is presented. It is based on multi-population algorithms and allows to select not only parameters of control systems, but also its structure. Proposed approach was tested on a problem of stabilization of double spring-mass-damp object.

In this paper we propose a new approach to nonlinear modelling. It uses capabilities ofthe so-called flexible neuro-fuzzy systems and evolutionary algorithms. The aim of our method is not only to achieve appropriate accuracy of the model, but also to ensure the possibility of interpretability of the knowledge within it. The proposed approach was ac...

In this paper a new method for designing neuro-fuzzy systems for nonlinear modelling is proposed. This method contains a complex weighted fitness function with interpretability criteria and new enhanced tuning process for selecting parameters and structure of the system based on a hybrid population-based algorithm (composed of evolutionary strategy...

In this paper we propose a new approach for selection of the structure and parameters of the control system. Proposed approach is based on the selected population-based algorithms. In this approach we considered a combination of the genetic algorithm (it is used for selection of structure of the control system) fused with one of the following algor...

In this paper we propose a new method for evolutionary selection of parameters and structure of neuro-fuzzy system for nonlinear modelling. This method allows maintain the correct proportions between accuracy, complexity and interpretability of the system. Our algorithm has been tested using well-known benchmarks.

Methods using dynamic signature for identity verification may be divided into three main categories: global methods, local function based methods and regional function based methods. Global methods base on a set of global parametric features, which are extracted from signature of user. Global feature extraction methods have been often presented in...

In the process of designing automatic control system it is very important to have an accurate model of the controlled process. Approaches to modelling dynamic systems presented in the literature are often approximate, uninterpretable (acting as a black box), not appropriate to work in real-time, so it is not possible to create a hardware emulator o...