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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:
Lightweight hybrid cryptography algorithm for wireless body area sensor networks using cipher technique
Autorzy:
Raziq, Aizaz
Qureshi, Kashif Naseer
Yar, Asfand
Ghafoori, Kayhan Zrar
Jeon, Gwanggil
Powiązania:
https://bibliotekanauki.pl/articles/38708768.pdf
Data publikacji:
2024
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
WBAN
healthcare
security
data
network
routing
cryptography
light-weight
mechanism
opieka zdrowotna
bezpieczeństwo
dane
sieć
trasowanie
kryptografia
mechanizm
Opis:
Wireless Body Area Networks (WBANs) are based on connected and dedicated sensor nodes for patient monitoring in the healthcare sector. The sensor nodes are implanted inside or outside the patient’s body for sensing the vital signs and transmitting the sensed data to the end devices for decision-making. These sensor nodes use advanced communication technologies for data communication. However, they have limited capabilities in terms of computation power, battery life, storage, and memory, and these constraints make networks more vulnerable to security breaches and routing challenges. Important and sensitive information is exchanged over an unsecured channel in the network. Several devices are involved in handling the data in WBANs, including sink nodes, coordinator, or gateway nodes. Many cryptographic schemes have been introduced to ensure security in WBANs by using traditional confidentiality and key-sharing strategies. However, these techniques are not suitable for limited resource-based sensor nodes. In this paper, we propose a Lightweight Hybrid Cryptography Algorithm (LWHCA) that uses cryptographicbased techniques for WBAN networks to improve network security, minimize network overhead and delay issues, and improve the healthcare monitoring processes. The proposed solution is evaluated in a simulation scenario and compared with state-of-the-art schemes in terms of energy consumption, and ciphertext size.
Źródło:
Computer Assisted Methods in Engineering and Science; 2024, 31, 2; 213-240
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
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 contemporary multi-objective feature selection model for depression detection using a hybrid pBGSK optimization algorithm
Autorzy:
Kavi Priya, Santhosam
Pon Karthika, Kasirajan
Powiązania:
https://bibliotekanauki.pl/articles/2201021.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
depression detection
text classification
dimensionality reduction
hybrid feature selection
wykrywanie depresji
klasyfikacja tekstu
redukcja wymiarowości
wybór funkcji
Opis:
Depression is one of the primary causes of global mental illnesses and an underlying reason for suicide. The user generated text content available in social media forums offers an opportunity to build automatic and reliable depression detection models. The core objective of this work is to select an optimal set of features that may help in classifying depressive contents posted on social media. To this end, a novel multi-objective feature selection technique (EFS-pBGSK) and machine learning algorithms are employed to train the proposed model. The novel feature selection technique incorporates a binary gaining-sharing knowledge-based optimization algorithm with population reduction (pBGSK) to obtain the optimized features from the original feature space. The extensive feature selector (EFS) is used to filter out the excessive features based on their ranking. Two text depression datasets collected from Twitter and Reddit forums are used for the evaluation of the proposed feature selection model. The experimentation is carried out using naive Bayes (NB) and support vector machine (SVM) classifiers for five different feature subset sizes (10, 50, 100, 300 and 500). The experimental outcome indicates that the proposed model can achieve superior performance scores. The top results are obtained using the SVM classifier for the SDD dataset with 0.962 accuracy, 0.929 F1 score, 0.0809 log-loss and 0.0717 mean absolute error (MAE). As a result, the optimal combination of features selected by the proposed hybrid model significantly improves the performance of the depression detection system.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 1; 117--131
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer 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 heuristic algorithm for equipment scheduling at an automated container terminal with multi-size containers
Autorzy:
Li, Hui
Powiązania:
https://bibliotekanauki.pl/articles/27311782.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
automated container terminal
multi-size containers
yard cranes
energy consumption
planowanie zintegrowane
kontenery
żurawie stoczniowe
zużycie energii
Opis:
With the increasing volume of shipping containers, container multimodal transport and port scheduling have attracted much attention. The allocation and dispatching of handling equipment to minimize completion time and energy consumption have always been a focus of research. This paper considers a scheduling problem at an automated land-maritime multimodal container terminal with multi-size containers, in which operating facilities and equipment such as quay cranes, vehicles, yard cranes, and external container trucks are involved. Moreover, the diversity of container sizes and the location of handshake areas in yards are concerned. A mixed integer programming model is established to schedule all operating facilities and equipment. To solve the mathematical model is a NP-hard problem, which is difficult to be solved by conventional methods. Then we propose a heuristic algorithm which merges multiple targets into one and designs an improved genetic algorithm based on the heuristic combination strategy in which 20-ft containers are paired-up to the same yard before allocation. After that, some experiments are designed to prove the effectiveness of the model and the algorithm. The effect of configurations on efficiency and energy consumption under different conditions is discussed, and the influences of different parameters and the proportion of 20-ft containers are also compared. Furthermore, the influence of locations of handshake area with different yard quantities are compared. To conclude, there is an optimal number of equipment to be allocated. If few equipment is used, the operation time will be prolonged; if too many, the energy consumption will be increased. When the yard operation is the bottleneck, the handover location should be in the centre, otherwise other locations might be feasible. When the proportion of 20-ft containers that can be combined is large, the method proposed in this paper has advantages over traditional methods. The proposed algorithm has made a breakthrough in improving efficiency and reducing energy consumption.
Źródło:
Archives of Transport; 2023, 65, 1; 67--86
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid evolutionary algorithm of optimized controller placement in SDN environment
Autorzy:
Hemagowri, J.
Tamil Selvan, P.
Powiązania:
https://bibliotekanauki.pl/articles/38704829.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
controller
software defined network
Gaussian chaotic map
fish swarm
multi-criteria optimization
kontroler
sieć zdefiniowana programowo
mapa chaosu Gaussa
rój ryb
optymalizacja wielokryterialna
Opis:
Controller placement problem (CPP) is a significant technological challenge in software defined network (SDN). Deployment of a properly designed SDN-based network is required to detect optimal number of controllers for enhancing the network’s performance. However, the best possible controller placement for enhancing the network’s performance faces many issues. To solve the CPP, a novel technique called the hybrid evolutionary algorithm of optimized controller placement (HEA-OCP) in SDN environment is introduced to increase network’s performance by different network topologies. In the proposed model, optimized controller placement using improved multi-objective artificial fish optimization is employed to improve data transmission and reduce latency. Controller placement can be determined using an undirected graph based on a variety of factors, including propagation delay, load balancing capabilities and bandwidth, fault tolerance and data transfer rate, and a variety of other factors. For each controller, the fitness value is calculated over multi-criteria functions. The optimizer’s performance can be improved with the use of Gaussian chaotic maps. In large-scale SDN networks using HEC-OCP, the algorithm dynamically analyzes the optimal number of controllers and the best connections between switches and controllers. As a result, the overall network performance is improved and the delay minimization-based controller placement strategy is obtained. The simulation of HEA-OCP with existing methods is conducted by a network topology dataset of various metrics, namely packet delivery ratio, packet drop rate, throughput, average latency, and jitter. The proposed HEA-OCP improves the packet delivery and throughput with reduced average latency, and packet drop ensures more instantaneous communications in real-time applications of SDN for better decision-making.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 4; 539-556
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
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
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