Dane kontaktowe:
Pokój: 517
Stanowisko:
Adiunkt naukowo-dydaktyczny
Zespoły badawcze:
Nowe systemy głębokiego uczenia i ich zastosowania
Prowadzone zajęcia:
Paradygmaty programowania lab
Zastosowanie sztucznej inteligencji w urządzeniach mobilnych lab
Zastosowanie sztucznej inteligencji w urządzeniach mobilnych wyk
Interaktywna grafika i prezentacja danych wyk
Interaktywna grafika i prezentacja danych lab
Evolutionary algorithms & search strategies proj
Evolutionary algorithms & search strategies lab
Evolutionary algorithms & search strategies wyk
Administrowanie internetowymi serwerami baz danych lab
Administrowanie internetowymi serwerami baz danych wyk
Bezpieczeństwo sieci komputerowych lab
Bezpieczeństwo sieci komputerowych wyk
Algorytmy ewolucyjne i strategie przeszukiwań lab
Algorytmy ewolucyjne i strategie przeszukiwań wyk
dr inż.
Piotr Dziwiński
Konsultacje: Poniedziałek 10:00 - 12:00 (pok. 517 lub zdalnie przy użyciu BBB)
Urodził się w Zawierciu (woj. Śląskie) w 1978 roku. W latach 1998-2003 studiował na Wydziale Inżynierii Mechanicznej i Informatyki Politechniki Częstochowskiej na kierunku Informatyka uzyskując stopień magistra inżyniera w 2003 roku. W październiku 2003 roku rozpoczął studia doktoranckie w dyscyplinie informatyka uzyskując tytuł naukowy doktora nauk technicznych w dyscyplinie informatyka w roku 2008. Od 1 września 2008 jest zatrudniony na stanowisku adiunkta w Katedrze Inteligentnych Systemów Informatycznych na Wydziale Inżynierii Mechanicznej i Informatyki Politechniki Częstochowskiej. Prywatnie, jak również zawodowo jest pasjonatem programowania, sztucznej inteligencji, w szczególności algorytmów czerpiących inspirację z tzw. kolektywnej inteligencji.
Zainteresowania naukowe:
- algorytmy mrówkowe,
- algorytmy bazujące na kolektywnej inteligencji,
- algorytmy hybrydowe bazujące na PSO,
- systemy rozmyte i neuronowo-rozmyte,
- sztuczne sieci neuronowe,
- modelowanie nieliniowe,
- sprzętowa implementacja systemów neuronowo-rozmytych.
Publikacje (24)
2023 (1)
Dziwinski P., Bartczuk L., A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm with Self-Adaptation Mechanism. (0)
A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm with Self-Adaptation Mechanism
, A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm with Self-Adaptation Mechanism, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 363-374, 2023, Liczba cytowań: 02022 (2)
Galkowski T., Krzyzak A., Dziwinski P., Fast Estimation of Multidimensional Regression Functions. (1)
Fast Estimation of Multidimensional Regression Functions
, Fast Estimation of Multidimensional Regression Functions, 2022 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022, 211-216, 2022, Liczba cytowań: 1
Hammad M., Meshoul S., Dziwinski P., Plawiak P., Elgendy I.A., Efficient Lightweight Multimodel Deep Fusion Based on ECG for Arrhythmia Classification. (9)
Efficient Lightweight Multimodel Deep Fusion Based on ECG for Arrhythmia Classification
, Efficient Lightweight Multimodel Deep Fusion Based on ECG for Arrhythmia Classification, Sensors, 22, 22, 2022, Liczba cytowań: 92021 (1)
Dziwinski P., Przybyl A., Trippner P., Paszkowski J., Hayashi Y., Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm. (10)
Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm
, Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 243-266, 2021, Liczba cytowań: 102020 (3)
Dziwinski P., Bartczuk L., A New Hybrid Particle Swarm Optimization and Genetic Algorithm Method Controlled by Fuzzy Logic. (69)
A New Hybrid Particle Swarm Optimization and Genetic Algorithm Method Controlled by Fuzzy Logic
, A New Hybrid Particle Swarm Optimization and Genetic Algorithm Method Controlled by Fuzzy Logic, IEEE Transactions on Fuzzy Systems, 28, 28, 1140-1154, 2020, Liczba cytowań: 69
Bartczuk L., Dziwinski P., Goetzen P., Nonlinear Fuzzy Modelling of Dynamic Objects with Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm. (1)
Nonlinear Fuzzy Modelling of Dynamic Objects with Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm
, Nonlinear Fuzzy Modelling of Dynamic Objects with Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 315-325, 2020, Liczba cytowań: 1
Dziwinski P., Bartczuk L., Paszkowski J., A New Auto Adaptive Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm. (15)
A New Auto Adaptive Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm
, A New Auto Adaptive Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 95-111, 2020, Liczba cytowań: 152019 (1)
Dziwinski P., Bartczuk L., Goetzen P., A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm. (6)
A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm
, A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 432-444, 2019, Liczba cytowań: 62018 (2)
Dziwinski P., Bartczuk L., Przybyszewski K., A population based algorithm and fuzzy decision trees for nonlinear modeling. (4)
A population based algorithm and fuzzy decision trees for nonlinear modeling
, A population based algorithm and fuzzy decision trees for nonlinear modeling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 516-531, 2018, Liczba cytowań: 4
Bartczuk L., Dziwinski P., Cader A., Symbolic regression with the AMSTA+GP in a non-linear modelling of dynamic objects. (0)
Symbolic regression with the AMSTA+GP in a non-linear modelling of dynamic objects
, Symbolic regression with the AMSTA+GP in a non-linear modelling of dynamic objects, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 504-515, 2018, Liczba cytowań: 02017 (2)
Bartczuk L., Dziwinski P., Red'Ko V.G., The concept on nonlinear modelling of dynamic objects based on state transition algorithm and genetic programming. (6)
The concept on nonlinear modelling of dynamic objects based on state transition algorithm and genetic programming
, The concept on nonlinear modelling of dynamic objects based on state transition algorithm and genetic programming, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 209-220, 2017, Liczba cytowań: 6
Dziwinski P., Bartczuk L., Tingwen H., A method for non-linear modelling based on the capabilities of PSO and GA algorithms. (5)
A method for non-linear modelling based on the capabilities of PSO and GA algorithms
, A method for non-linear modelling based on the capabilities of PSO and GA algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 221-232, 2017, Liczba cytowań: 52016 (2)
Dziwinski P., Avedyan E.D., A new approach for using the fuzzy decision trees for the detection of the significant operating points in the nonlinear modeling. (6)
A new approach for using the fuzzy decision trees for the detection of the significant operating points in the nonlinear modeling
, A new approach for using the fuzzy decision trees for the detection of the significant operating points in the nonlinear modeling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 279-292, 2016, Liczba cytowań: 6
Dziwinski P., Avedyan E.D., A new method of the intelligent modeling of the nonlinear dynamic objects with fuzzy detection of the operating points. (15)
A new method of the intelligent modeling of the nonlinear dynamic objects with fuzzy detection of the operating points
, A new method of the intelligent modeling of the nonlinear dynamic objects with fuzzy detection of the operating points, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 293-305, 2016, Liczba cytowań: 152015 (1)
Dziwinski P., Avedyan E.D., A new approach to nonlinear modeling based on significant operating points detection. (18)
A new approach to nonlinear modeling based on significant operating points detection
, A new approach to nonlinear modeling based on significant operating points detection, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 364-378, 2015, Liczba cytowań: 182014 (1)
Dziwinski P., Bartczuk L., Przybyl A., Avedyan E.D., A new algorithm for identification of significant operating points using swarm intelligence. (32)
A new algorithm for identification of significant operating points using swarm intelligence
, A new algorithm for identification of significant operating points using swarm intelligence, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 349-362, 2014, Liczba cytowań: 322013 (1)
Bartczuk L., Przybyl A., Dziwinski P., Hybrid state variables - Fuzzy logic modelling of nonlinear objects. (19)
Hybrid state variables - Fuzzy logic modelling of nonlinear objects
, Hybrid state variables - Fuzzy logic modelling of nonlinear objects, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 227-234, 2013, Liczba cytowań: 192012 (2)
Dziwinski P., Bartczuk L., Starczewski J.T., Fully controllable ant colony system for text data clustering. (26)
Fully controllable ant colony system for text data clustering
, Fully controllable ant colony system for text data clustering, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7269 LNCS, 7269 LNCS, 199-205, 2012, Liczba cytowań: 26
Bartczuk L., Dziwinski P., Starczewski J.T., A new method for dealing with unbalanced linguistic term set. (26)
A new method for dealing with unbalanced linguistic term set
, A new method for dealing with unbalanced linguistic term set, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 207-212, 2012, Liczba cytowań: 262010 (3)
Bartczuk L., Dziwinski P., Starczewski J.T., New method for generation type-2 fuzzy partition for FDT. (16)
New method for generation type-2 fuzzy partition for FDT
, New method for generation type-2 fuzzy partition for FDT, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 275-280, 2010, Liczba cytowań: 16
Dziwinski P., Starczewski J.T., Bartczuk L., New linguistic hedges in construction of interval type-2 FLS. (14)
New linguistic hedges in construction of interval type-2 FLS
, New linguistic hedges in construction of interval type-2 FLS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 445-450, 2010, Liczba cytowań: 14
Starczewski J.T., Bartczuk L., Dziwinski P., Marvuglia A., Learning methods for type-2 FLS based on FCM. (20)
Learning methods for type-2 FLS based on FCM
, Learning methods for type-2 FLS based on FCM, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 224-231, 2010, Liczba cytowań: 202008 (1)
Dziwinski P., Rutkowska D., Ant focused crawling algorithm. (14)
Ant focused crawling algorithm
, Ant focused crawling algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 1018-1028, 2008, Liczba cytowań: 142006 (1)
Dziwinski P., Rutkowska D., Algorithm for generating fuzzy rules for WWW document classification. (17)
