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Tytuł:
Analiza wybranych metod walidacji krzyżowej w programie RSES
Analysis of selected cross-validation methods in the RSES program
Autorzy:
Kołpacki, Radosław
Powiązania:
https://bibliotekanauki.pl/articles/41203506.pdf
Data publikacji:
2024
Wydawca:
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Tematy:
walidacja krzyżowa
RSES
analiza danych
zależność
algorytm genetyczny
cross-validation
data analysis
dependency
genetic algorithm
Opis:
W artykule przeprowadzono analizę zbioru danych za pomocą dwóch metod walidacji krzyżowej. Wykorzystano program RSES do identyfikacji kluczowych właściwości i relacji w zbiorze. Wyniki wykazują wpływ niektórych parametrów na potencjalną dokładność wyników.
This article presents an analysis of a dataset using two cross-validation methods. The RSES program was employed to identify key properties and relationships within the dataset. The results indicate the impact of certain parameters on the potential accuracy of the outcomes.
Źródło:
Studia i Materiały Informatyki Stosowanej; 2024, 16, 1
1689-6300
Pojawia się w:
Studia i Materiały Informatyki Stosowanej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analiza wybranych metod walidacji krzyżowej w programie RSES
Analysis of selected cross-validation methods in the RSES program
Autorzy:
Bethke, Beata
Powiązania:
https://bibliotekanauki.pl/articles/41203515.pdf
Data publikacji:
2024
Wydawca:
Uniwersytet Kazimierza Wielkiego w Bydgoszczy
Tematy:
walidacja krzyżowa
RSES
analiza danych
zależność
algorytm genetyczny
cross-validation
data analysis
dependency
genetic algorithm
Opis:
W artykule przeprowadzono analizę zbioru danych za pomocą dwóch metod walidacji krzyżowej. Wykorzystano program RSES do identyfikacji kluczowych właściwości i relacji w zbiorze. Wyniki wykazują wpływ niektórych parametrów na potencjalną dokładność wyników.
This article presents an analysis of a dataset using two cross-validation methods. The RSES program was employed to identify key properties and relationships within the dataset. The results indicate the impact of certain parameters on the potential accuracy of the outcomes.
Źródło:
Studia i Materiały Informatyki Stosowanej; 2024, 16, 1; 11-14
1689-6300
Pojawia się w:
Studia i Materiały Informatyki Stosowanej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applicability of artificial intelligence in smart healthcare systems for automatic detection of Parkinson’s Disease
Autorzy:
Pallathadka, Harikumar
Padminivalli V., S.J.R.K.
Vasavi, M.
Nancy, P.
Naved, Mohd
Kumar, Harish
Ray, Samrat
Powiązania:
https://bibliotekanauki.pl/articles/38709253.pdf
Data publikacji:
2024
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
Parkinson’s disease
detection
machine learning
relief algorithm
LDA algorithm
SVM-RBF
accuracy
sensitivity
specificity
choroba Parkinsona
wykrywanie
nauczanie maszynowe
algorytm ulgi
Algorytm LDA
dokładność
wrażliwość
specyficzność
Opis:
Parkinson’s disease is associated with memory loss, anxiety, and depression in the brain. Problems such as poor balance and difficulty during walking can be observed in addition to symptoms of impaired posture and rigidity. The field dedicated to making computers capable of learning autonomously, without having to be explicitly programmed, is known as machine learning. An approach to the diagnosis of Parkinson’s disease, which is based on artificial intelligence, is discussed in this article. The input for this system is provided through photographic examples of Parkinson’s disease patient handwriting. Received photos are preprocessed using the relief feature option to begin the process. This is helpful in the process of selecting characteristics for the identification of Parkinson’s disease. After that, the linear discriminant analysis (LDA) algorithm is employed to reduce the dimensions, bringing down the total number of dimensions that are present in the input data. The photos are then classified via radial basis function-support vector machine (SVM-RBF), k-nearest neighbors (KNN), and naive Bayes algorithms, respectively.
Źródło:
Computer Assisted Methods in Engineering and Science; 2024, 31, 2; 175-185
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of RRAP reliability optimization as a test of nature-inspired algorithms
Autorzy:
Pieprzycki, Adam
Filipowicz, Bogusław
Powiązania:
https://bibliotekanauki.pl/articles/35533466.pdf
Data publikacji:
2024-02-15
Wydawca:
Akademia Tarnowska
Tematy:
reliability optimization
RRAP
Firefly Algorithm (FA)
Cuckoo Search (CS)
ANOVA
Lévy flight
Opis:
This paper presents a discussion on the application of two swarm intelligence algorithms, Cuckoo Search (CS) and Firey Algorithm (FA), to maximize the reliability of two complex systems with resource constraints, which have been well-known in the literature. The reliability of the systems is also evaluated using several classical methods. The results indicate that although the CS algorithm, which utilizes Lévy flight, is eective, the FA rey algorithm outperformed it in the presented optimization tasks, within the given parameter range. These ndings contribute to the ongoing discussion on using nature-inspired algorithms for solving Reliability Redundancy Allocation Problem (RRAP) problems, and the two test scenarios used in the study can be useful for validating other algorithms in RRAP problems. The paper introduces metrics and methods for analyzing and comparing the performance of algorithms in RRAP optimization, including the comparison of criterion function values and other parameters introduced in the paper. Additionally, the paper discusses statistical analyses of variance (ANOVA) with post-hoc RIR Tuckey tests.
Źródło:
Science, Technology and Innovation; 2023, 18, 3-4; 1-14
2544-9125
Pojawia się w:
Science, Technology and Innovation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial intelligence-powered pulse sequences in nuclear magnetic resonance and magnetic resonance imaging: historical trends, current innovations and perspectives
Autorzy:
Tokarz, Paweł
Powiązania:
https://bibliotekanauki.pl/articles/35508129.pdf
Data publikacji:
2024
Wydawca:
Radomskie Towarzystwo Naukowe
Tematy:
artificial intelligence
machine learning
evolutionary algorithm
artificial neural network
nuclear magnetic resonance
magnetic resonance imaging
pulse sequence
shaped pulse
sztuczna inteligencja
uczenie maszynowe
algorytm ewolucyjny
sztuczna sieć neuronowa
magnetyczny rezonans jądrowy
rezonans magnetyczny
sekwencja impulsów
impuls ukształtowany
Opis:
This review article explores the historical background and recent advances in the application of artificial intelligence (AI) in the development of radiofrequency pulses and pulse sequences in nuclear magnetic resonance spectroscopy (NMR) and imaging (MRI). The introduction of AI into this field, which traces back to the late 1970s, has recently witnessed remarkable progress, leading to the design of specialized frameworks and software solutions such as DeepRF, MRzero, and GENETICS-AI. Through an analysis of literature and case studies, this review tracks the transformation of AI-driven pulse design from initial proof-of-concept studies to comprehensive scientific programs, shedding light on the potential implications for the broader NMR and MRI communities. The fusion of artificial intelligence and magnetic resonance pulse design stands as a promising frontier in spectroscopy and imaging, offering innovative enhancements in data acquisition, analysis, and interpretation across diverse scientific domains.
Źródło:
Scientiae Radices; 2024, 3, 1; 30-52
2956-4808
Pojawia się w:
Scientiae Radices
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Noninvasive blood glucose level monitoring for predicting insulin infusion rate using multivariate data
Autorzy:
Geetha, G.
Ponsam, J. Godwin
Nimala, K.
Powiązania:
https://bibliotekanauki.pl/articles/38709458.pdf
Data publikacji:
2024
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
CGM
fog computing
hypoglycemia
hyperglycemia
Apriori algorithm
obliczenie mgły
hipoglikemia
hiperglikemia
Algorytm Apriori
Opis:
Diabetes stands as the most widely recognized acute disease globally, resulting in death when it is not treated in an appropriate manner and time. We have developed a closedloop control system that uses continuous glucose, carbohydrate, and physiological variable data to regulate glucose levels and treat hyperglycemia and hypoglycemia, as well as a hypoglycemia early warning module. Overall, the proposed models are effective at predicting a normal glycemic range from >70 to 180 mg/dl, hypoglycemic values of <70 mg/dl, and hyperglycemic value of 180 mg/dl blood sugar levels. We undertook a seven-day, day-and-night home study with 15 adults. Initially, we started with checking insulin levels after meal consumption, and later, we concentrated on how our system reacted to the physical activity of the patients. Evaluation was conducted based on performance parameters such as precision (0.87), recall (0.87), F-score (0.82), delay (26.5±3), and error size (1.14±2).
Źródło:
Computer Assisted Methods in Engineering and Science; 2024, 31, 2; 157-174
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A generative approach to hull design for a small watercraft
Autorzy:
Karczewski, Artur
Kozak, Janusz
Powiązania:
https://bibliotekanauki.pl/articles/32917891.pdf
Data publikacji:
2023
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
method
generative design
yacht
optimisation
genetic algorithm
Opis:
In the field of ocean engineering, the task of spatial hull modelling is one of the most complicated problems in ship design. This study presents a procedure applied as a generative approach to the design problems for the hull geometry of small vessels using elements of concurrent design with multi-criteria optimisation processes. Based upon widely available commercial software, an algorithm for the mathematical formulation of the boundary conditions, the data flow during processing and formulae for the optimisation processes are developed. As an example of the application of this novel approach, the results for the hull design of a sailing yacht are presented.
Źródło:
Polish Maritime Research; 2023, 1; 4-12
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A genetic algorithm based optimized convolutional neural network for face recognition
Autorzy:
Karlupia, Namrata
Mahajan, Palak
Abrol, Pawanesh
Lehana, Parveen K.
Powiązania:
https://bibliotekanauki.pl/articles/2201023.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
convolutional neural network
genetic algorithm
deep learning
evolutionary technique
sieć neuronowa konwolucyjna
algorytm genetyczny
uczenie głębokie
technika ewolucyjna
Opis:
Face recognition (FR) is one of the most active research areas in the field of computer vision. Convolutional neural networks (CNNs) have been extensively used in this field due to their good efficiency. Thus, it is important to find the best CNN parameters for its best performance. Hyperparameter optimization is one of the various techniques for increasing the performance of CNN models. Since manual tuning of hyperparameters is a tedious and time-consuming task, population based metaheuristic techniques can be used for the automatic hyperparameter optimization of CNNs. Automatic tuning of parameters reduces manual efforts and improves the efficiency of the CNN model. In the proposed work, genetic algorithm (GA) based hyperparameter optimization of CNNs is applied for face recognition. GAs are used for the optimization of various hyperparameters like filter size as well as the number of filters and of hidden layers. For analysis, a benchmark dataset for FR with ninety subjects is used. The experimental results indicate that the proposed GA-CNN model generates an improved model accuracy in comparison with existing CNN models. In each iteration, the GA minimizes the objective function by selecting the best combination set of CNN hyperparameters. An improved accuracy of 94.5% is obtained for FR.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 1; 21--31
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A genetic algorithm-based approach for flexible job shop rescheduling problem with machine failure interference
Autorzy:
Liang, Zhongyuan
Zhong, Peisi
Zhang, Chao
Yang, Wenlei
Xiong, Wei
Yang, Shihao
Meng, Jing
Powiązania:
https://bibliotekanauki.pl/articles/27320976.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
genetic algorithm
rescheduling
machine failure
flexible job shop scheduling
Opis:
Rescheduling is the guarantee to maintain the reliable operation of production system process. In production system, the original scheduling scheme cannot be carried out when machine breaks down. It is necessary to transfer the production tasks in the failure cycle and replan the production path to ensure that the production tasks are completed on time and maintain the stability of production system. To address this issue, in this paper, we studied the event-driven rescheduling policy in dynamic environment, and established the usage rules of right-shift rescheduling and complete rescheduling based on the type of interference events. And then, we proposed the rescheduling decision method based on genetic algorithm for solving flexible job shop scheduling problem with machine fault interference. In addition, we extended the "mk" series of instances by introducing the machine fault interference information. The solution data show that the complete rescheduling method can respond effectively to the rescheduling of flexible job shop scheduling problem with machine failure interference.
Źródło:
Eksploatacja i Niezawodność; 2023, 25, 4; art. no. 171784
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Linguistic Analysis of Sexism-Related Hate Speech in Social Media
Lingwistyczna analiza mowy nienawiści związanej z seksizmem w mediach społecznościowych
Autorzy:
Bugajska, Anna
Dziedzic, Paulina
Powiązania:
https://bibliotekanauki.pl/articles/37277295.pdf
Data publikacji:
2023
Wydawca:
Akademia Ignatianum w Krakowie
Tematy:
mowa nienawiści
algorytm
media społecznościowe
język
seksizm
hate speech
algorithm
social media
language
sexism
Opis:
The aim of this article is to present the functioning of a dual algorithm/human analysis and to investigate the means with which to study hate speech, especially sexism-related hate speech, in the online environment, focusing on social media comments and hashtags. Another aim is to investigate new linguistic trends in contemporary online hate speech that can be revealed via quantitative hate speech analysis. In the first part, the concept of hate speech is briefly introduced in a linguistic context. In the second part, an example of a Twitter hashtag is analyzed. In the third part, an algorithm for the identification of sexism-related hate speech from the corpus available at hatespeechdata.com is discussed. The article demonstrates the methods of evaluating selected types of online content for the presence of hate speech. It is made evident that algorithm-based hate speech qualification is an insufficient tool for identifying hate speech and that qualitative analysis by a trained linguist is necessary.
Artykuł ma na celu przedstawienie funkcjonowania analizy dualnej algorytm-człowiek oraz sposobów badania w szczególności mowy nienawiści związanej z seksizmem w środowisku internetowym, z naciskiem na komentarze i hashtagi w mediach społecznościowych, oraz zbadanie nowych trendów językowych we współczesnej mowie nienawiści w Internecie, które można ujawnić za pomocą ilościowej analizy mowy nienawiści. W pierwszej części pokrótce wprowadzono pojęcie mowy nienawiści, odnosząc się do kontekstu językowego. W drugiej części przeanalizowano przykładowy hashtag Twittera. W trzeciej części wykorzystano algorytm identyfikacji mowy nienawiści na tle seksizmu z korpusu dostępnego na stronie hatespeechdata.com. W artykule przedstawiono metody oceny wybranych typów treści internetowych pod kątem obecności mowy nienawiści. Zostaje dowiedzione, że algorytmiczna kwalifikacja mowy nienawiści jest niewystarczającym narzędziem w identyfikacji mowy nienawiści i konieczna jest analiza jakościowa przeszkolonego językoznawcy.
Źródło:
Perspektywy Kultury; 2023, 42, 3; 549-560
2081-1446
2719-8014
Pojawia się w:
Perspektywy Kultury
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A method of lower and upper solutions for control problems and application to a model of bone marrow transplantation
Autorzy:
Parajdi, Lorand Gabriel
Precup, Radu
Haplea, Ioan Ştefan
Powiązania:
https://bibliotekanauki.pl/articles/24200690.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
control problem
lower and upper solution
fixed point
approximation algorithm
numerical solution
medical application
sterowanie optymalne
punkt stały
algorytm aproksymacyjny
rozwiązanie numeryczne
zastosowanie medyczne
Opis:
A lower and upper solution method is introduced for control problems related to abstract operator equations. The method is illustrated on a control problem for the Lotka-Volterra model with seasonal harvesting and applied to a control problem of cell evolution after bone marrow transplantation.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 3; 409--418
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A nature inspired collision avoidance algorithm for ships
Autorzy:
Lazarowska, A.
Powiązania:
https://bibliotekanauki.pl/articles/24201448.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
collision avoidance algorithm
safe own Ship's Trajectory
safe navigation
ant colony optimization
firefly agorithm
path planning
swarm intelligence
nature inspired computing
Opis:
Nature inspired algorithms are regarded as a powerful tool for solving real life problems. They do not guarantee to find the globally optimal solution, but can find a suboptimal, robust solution with an acceptable computational cost. The paper introduces an approach to the development of collision avoidance algorithms for ships based on the firefly algorithm, classified to the swarm intelligence methods. Such algorithms are inspired by the swarming behaviour of animals, such as e.g. birds, fish, ants, bees, fireflies. The description of the developed algorithm is followed by the presentation of simulation results, which show, that it might be regarded as an efficient method of solving the collision avoidance problem. Such algorithm is intended for use in the Decision Support System or in the Collision Avoidance Module of the Autonomous Navigation System for Maritime Autonomous Surface Ships.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 2; 341--346
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Nature Inspired Hybrid Partitional Clustering Method Based on Grey Wolf Optimization and JAYA Algorithm
Autorzy:
Shial, Gyanaranjan
Saho, Sabita
Panigrahi, Sibarama
Powiązania:
https://bibliotekanauki.pl/articles/27312857.pdf
Data publikacji:
2023
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
grey wolf optimizer
JAYA algorithm
article swarm optimization
ine-cosinealgorithm
partitional clustering
Opis:
This paper presents a hybrid meta-heuristic algorithm that uses the grey wolfoptimization (GWO) and the JAYA algorithm for data clustering. The ideais to use the explorative capability of the JAYA algorithm in the exploitativephase of GWO to form compact clusters. Here, instead of using only one bestand one worst solution for generating offspring, the three best wolves (alpha,beta and delta) and three worst wolves of the population are used. So, the bestand worst wolves assist in moving towards the most feasible solutions and simul-taneously it helps to avoid from worst solutions; this enhances the chances oftrapping at local optimal solutions. The superiority of the proposed algorithmis compared with five promising algorithms; namely, the sine-cosine (SCA),GWO, JAYA, particle swarm optimization (PSO), and k-means algorithms.The performance of the proposed algorithm is evaluated for 23 benchmarkmathematical problems using the Friedman and Nemenyi hypothesis tests. Ad-ditionally, the superiority and robustness of our proposed algorithm is testedfor 15 data clustering problems by using both Duncan's multiple range test andthe Nemenyi hypothesis test.
Źródło:
Computer Science; 2023, 24 (3); 361--405
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new method of decision making in multi-objective optimal placement and sizing of distributed generators in the smart grid
Autorzy:
Khoshayand, Hossein Ali
Wattanapongsakorn, Naruemon
Mahdavian, Mehdi
Ganji, Ehsan
Powiązania:
https://bibliotekanauki.pl/articles/2202555.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
backward-forward load distribution
fuzzy logic
iterative search algorithm
multi-objective optimization
shortest distance from the origin
weighted sum
Opis:
One of the most important aims of the sizing and allocation of distributed generators (DGs) in power systems is to achieve the highest feasible efficiency and performance by using the least number of DGs. Considering the use of two DGs in comparison to a single DG significantly increases the degree of freedom in designing the power system. In this paper, the optimal placement and sizing of two DGs in the standard IEEE 33-bus network have been investigated with three objective functions which are the reduction of network losses, the improvement of voltage profiles, and cost reduction. In this way, by using the backward-forward load distribution, the load distribution is performed on the 33-bus network with the power summation method to obtain the total system losses and the average bus voltage. Then, using the iterative search algorithm and considering problem constraints, placement and sizing are done for two DGs to obtain all the possible answers and next, among these answers three answers are extracted as the best answers through three methods of fuzzy logic, the weighted sum, and the shortest distance from the origin. Also, using the multi-objective non-dominated sorting genetic algorithm II (NSGA-II) and setting the algorithm parameters, thirty-six Pareto fronts are obtained and from each Pareto front, with the help of three methods of fuzzy logic, weighted sum, and the shortest distance from the origin, three answers are extracted as the best answers. Finally, the answer which shows the least difference among the responses of the iterative search algorithm is selected as the best answer. The simulation results verify the performance and efficiency of the proposed method.
Źródło:
Archives of Electrical Engineering; 2023, 72, 1; 253--271
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A novel hybrid cuckoo search algorithm for optimization of a line-start PM synchronous motor
Autorzy:
Knypiński, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/2204509.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
hybrid cuckoo search algorithm
heuristic algorithms
multi-objective optimization
permanent magnet synchronous motor
PMSM
algorytm kukułki hybrydowy
algorytm Cuckoo
algorytm heurystyczny
optymalizacja wielocelowa
silnik synchroniczny z magnesem trwałym
Opis:
The paper presents a novel hybrid cuckoo search (CS) algorithm for the optimization of the line-start permanent magnet synchronous motor (LSPMSM). The hybrid optimization algorithm developed is a merger of the heuristic algorithm with the deterministic Hooke–Jeeves method. The hybrid optimization procedure developed was tested on analytical benchmark functions and the results were compared with the classical cuckoo search algorithm, genetic algorithm, particle swarm algorithm and bat algorithm. The optimization script containing a hybrid algorithm was developed in Delphi Tiburón. The results presented show that the modified method is characterized by better accuracy. The optimization procedure developed is related to a mathematical model of the LSPMSM. The multi-objective compromise function was applied as an optimality criterion. Selected results were presented and discussed.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 1; art. no. e144586
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 1766

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