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EN
Digital signal processing, such as filtering, information extraction, and fusion of various results, is currently an integral part of advanced medical therapies. It is especially important in neurosurgery during deep-brain stimulation procedures. In such procedures, the surgical target is accessed using special electrodes while not being directly visible. This requires very precise identification of brain structures in 3D space throughout the surgery. In the case of deep-brain stimulation surgery for Parkinson’s disease (PD), the target area—the subthalamic nucleus (STN)—is located deep within the brain. It is also very small (just a few millimetres across), which makes this procedure even more difficult. For this reason, various signals are acquired, filtered, and finally fused, to provide the neurosurgeon with the exact location of the target. These signals come from preoperative medical imaging (such as MRI and CT), and from recordings of brain activity carried out during surgery using special brain-implanted electrodes. Using the method described in this paper, it is possible to construct a decision-support system that, during surgery, analyses signals recorded within the patient’s brain and classifies them as recorded within the STN or not. The constructed classifier discriminates signals with a sensitivity of 0.97 and a specificity of 0.96. The described algorithm is currently used for deep-brain stimulation surgeries among PD patients.
EN
The suitability of a land plot in a real estate market could be identified as a good investment because the land plot is deemed as popular. This activity is important for economic growth, who is one of the sustainable development goals. Mostly, all research in this field is focused on sustainability as well as the opinions of professionals. However, this field should be explored from another side which is based on real geodata. Criteria and its weight are very important in decision support systems. The correct criteria can help in selection of the best real estate object for an investment, but it is not only useful but also and a challenging task that has not yet been solved. The methods of research are data graphical analysis, correlation, decision supporting systems, etc. The research aims at determining the significance of the connections and using them as the criteria in the selected decision supporting method. In addition, it will be determined which decision supporting method defines the most suitable object for investment. These new criteria are proposed for operation in the land use models. Furthermore, it has been identified as one criterion, which is significant in the urban and agrarian territories. Also it turned out, that the land plot is the most active when it is as far from a densely built-up residential territory as possible and as close to a school, and when the land plot is as large as possible.
EN
This article discusses the results of studies using the developed artificial neural networks in the analysis of the occurrence of the four main mechanisms destroying the selected forging tools subjected to five different surface treatment variants (nitrided layer, pad welded layer and three hybrid layers, i.e. AlCrTiSiN, Cr/CrN and Cr/AlCrTiN). Knowledge of the forging tool durability, needed in the process of artificial neural network training, was included in the set of training data (about 800 records) derived from long-term comprehensive research carried out under industrial conditions. Based on this set, neural networks with different architectures were developed and the results concerning the intensity of the occurrence of thermal-mechanical fatigue, abrasive wear, mechanical fatigue and plastic deformation were generated for each type of the applied treatment relative to the number of forgings, pressure, friction path and temperature.
EN
The article herein presents the method and algorithms for forming the feature space for the base of intellectualized system knowledge for the support system in the cyber threats and anomalies tasks. The system being elaborated might be used both autonomously by cyber threat services analysts and jointly with information protection complex systems. It is shown, that advised algorithms allow supplementing dynamically the knowledge base upon appearing the new threats, which permits to cut the time of their recognition and analysis, in particular, for cases of hard-to-explain features and reduce the false responses in threat recognizing systems, anomalies and attacks at informatization objects. It is stated herein, that collectively with the outcomes of previous authors investigations, the offered algorithms of forming the feature space for identifying cyber threats within decisions making support system are more effective. It is reached at the expense of the fact, that, comparing to existing decisions, the described decisions in the article, allow separate considering the task of threat recognition in the frame of the known classes, and if necessary supplementing feature space for the new threat types. It is demonstrated, that new threats features often initially are not identified within the frame of existing base of threat classes knowledge in the decision support system. As well the methods and advised algorithms allow fulfilling the time-efficient cyber threats classification for a definite informatization object.
EN
The article presents conceptually scientific and methodological principles of agricultural management on the basis of Information Technologies. It has determined the main directions of using Information Technologies in Agricultural Manufacturing. It has systematically investigated the manufacturing by agricultural producers, and it has determined and stressed the main functions and relationships between the two systemic parts – technical and technological as well as organizational and technical. There have been determined the hierarchical structure of the configuration for the husbandry systems. It was explored that this configuration consists of nine main parts, and which of them have their own configuration. It was a conceptually determined processes of architecture management of agricultural programs (portfolios) and the configuration of agricultural products. The developed structural and project approach to configurations management of systemic parts for agricultural manufacturing is the part of scientific and methodological principles of this manufacturing management using Information Technologies.
PL
Artykuł przedstawia koncepcje naukowe i metodologiczne zasady zarządzania rolnictwem na podstawie technologii informacyjnych. Określono główne kierunki wykorzystania technologii informacyjnych w produkcji rolniczej. Systematycznie badano produkcję przez producentów rolnych. Ustalono i podkreślono główne funkcje i związki między dwiema częściami systemowymi – techniczną i technologiczną oraz organizacyjną i techniczną. Określono hierarchiczną strukturę konfiguracji systemu agrarnego. Zbadano, że ta konfiguracja składa się z dziewięciu głównych części, które mają własną konfigurację. Określono koncepcyjnie procesy zarządzania architekturą programów rolniczych (portfeli) i konfiguracji produktów rolnych. Opracowane podejście strukturalne i projektowe do zarządzania konfiguracjami części systemowych do produkcji rolniczej jest częścią naukowych i metodologicznych zasad zarządzania produkcją z wykorzystaniem technologii informatycznych.
6
Content available remote Spiking Neural Network Based on Cusp Catastrophe Theory
EN
This paper addresses the problem of effective processing using third generation neural networks. The article features two new models of spiking neurons based on the cusp catastrophe theory. The effectiveness of the models is demonstrated with an example of a network composed of three neurons solving the problem of linear inseparability of the XOR function. The proposed solutions are dedicated to hardware implementation using the Edge computing strategy. The paper presents simulation results and outlines further research direction in the field of practical applications and implementations using nanometer CMOS technologies and the current processing mode.
EN
The paper presents a method of supporting decision-making under risk by a risk- -averse decision-maker. Decision-making under risk occurs when the outcome of the system is ambiguous and depends on the state of the environment. The problem is considered as a multi-criteria optimization. The decision support method consists of interactive conduct of the process of decision-making. The decision is made by means of solving a problem with controlling parameters, which determine the aspirations of the decision-maker and evaluating the obtained solutions. The decision-maker sets parameters for which a solution is determined. Subsequently, he or she assesses the obtained solution, accepting or rejecting it. In the latter case, the decision-maker sets new values for the parameters and the problem is solved again. The present paper presents a discrete example of support for decision making under risk.
EN
Cross-docking is a strategy that distributes products directly from a supplier or manufacturing plant to a customer or retail chain, reducing handling or storage time. This study focuses on the truck scheduling problem, which consists of assigning each truck to a door at the dock and determining the sequences for the trucks at each door considering the time-window aspect. The study presents a mathematical model for door assignment and truck scheduling with time windows at multi-door cross-docking centers. The objective of the model is to minimize the overall earliness and tardiness for outbound trucks. Simulated annealing (SA) and tabu search (TS) algorithms are proposed to solve largesized problems. The results of the mathematical model and of meta-heuristic algorithms are compared by generating test problems for different sizes. A decision support system (DSS) is also designed for the truck scheduling problem for multi-door cross-docking centers. Computational results show that TS and SA algorithms are efficient in solving large-sized problems in a reasonable time.
PL
Pomimo dynamicznego rozwoju metod uczenia maszynowego i ich wdrażania do praktyki lekarskiej, automatyczna analiza znamion skórnych wciąż jest nierozwiązanym problemem. Poniższy artykuł proponuje zastosowanie algorytmu ewolucyjnego do zaprojektowania, wytrenowania i przetestowania całych populacji klasyfikatorów (sztucznych sieci neuronowych) oraz ich iteracyjnego udoskonalania w każdej kolejnej populacji, w celu osiągnięcia jak najlepszej dokładności klasyfikacji znamion skórnych. Algorytm zwraca optymalny zestaw cech opisujących obraz dermatoskopowy wraz z proponowaną architekturą sieci neuronowej. Uzyskano dokładność równą 85,83%, swoistość równą 79,07% oraz czułość równą 92,60%.
EN
Despite the dynamic development of machine learning methods, automatic analysis of skin lesions is still open issue. The following article proposes the use of an evolutionary algorithm to design, train, and to test a whole population of classifiers (artificial neural networks) and to iteratively improve them in each subsequent population, in order to achieve the best possible accuracy in the classification of skin lesions task. The algorithm returns an optimal set of features describing the dermatoscopic image together with the proposed architecture of the neural network. High classification results were obtained, in particular: accuracy equal to 85.83%, specificity 79.07% and sensitivity 92.60%.
PL
W artykule przedstawiono system ekspercki pomagający szkoleniowcom drużyny sportowej na optymalne obsadzenie danej pozycji w drużynie spośród dostępnych zawodników. System ten oparty jest o rozmytą metodę delficką, która na podstawie ocen sztabowców ocenia każdego z zawodników. Zawodnik z najwyższą notą jest rekomendowany na daną pozycję w drużynie. Działanie systemu przedstawiono na przykładzie obsadzenia pozycji napastnika w drużynie piłkarskiej w oparciu o oficjalne wytyczne Polskiego Związku Piłki Nożnej. Uzyskane wyniki sugerują, że proponowane rozwiązanie może być zastosowane do dowolnej zespołowej dyscypliny sportowej.
EN
The article presents expert system which helps coaches to optimal position setting in a team among all available players’. The system is based on fuzzy Delphi method which contains coaches raitings on each player. The highest note player is recommended on the specific position. The use of the system was presented on an example of striker position in football teat based on Polish Football Association model. Presented results shows that the solution can be implemented in any team sport discipline.
PL
W artykule przedstawiono system wspomagania decyzji pomagający bramkarzowi w obronie rzutu karnego. Wykorzystuje on zbiory rozmyte i podejście Bellmana-Zadeha do podejmowania decyzji. Zaproponowane rozwiązanie zostało zaimplementowane w postaci aplikacji webowej, która może zostać wykorzystana również w pokrewnych zagadnieniach dotyczących innych sportów zespołowych. Działanie aplikacji jak i realizacja algorytmu zostały przedstawione na przykładzie numerycznym.
EN
This article presents decision support system helping the goalkeeper in defending the penalty kicks. It is based on fuzzy sets and Bellman-Zadeh’s approach in decision making. The proposed solution was implemented in web application, which can be used in similar approaches in team sports. The application and realization of the algorithm was shown on numerical example.
EN
This article concerns a decision-support system based on artificial neural networks (ANN) enabling analysis and forecasting of the durability of forging tools used in the hot forging process of a cover forging – a sealing element of the driveshaft in road freight vehicles. The process of knowledge acquisition, adopted neural network architecture and parameters of the developed network are presented. In addition, 3 variants of a hybrid layer (gas nitrided layer GN + PVD coating) were applied to the selected tools (punches applied in the 2nd top forging operation): GN/AlCrTiN, GN/AlCrTiSiN, and GN/CrN, in order to improve durability, and the resultant tools were also compared to standard tools (with only gas nitriding) and regenerated tools (after repair welding regeneration). The indispensable knowledge about the durability of selected forging tools (after various surface engineering variants), required for the process of learning, testing and validation for various neural network architectures was obtained from comprehensive, multi-year studies. These studies covered, among other things: operational observation of the forging process, macroscopic analysis combined with scanning of tools’ working surfaces, microhardness measurements, microstructural analysis and numerical modeling of the forging process. The developed machine-learning dataset was a collection of approx. 900 knowledge records. The input (independent) variables were: number of forgings manufactures, pressing forces, temperature on selected tool surfaces, friction path and type of protective layer applied to tool. Meanwhile, output (dependent) variables were: geometrical loss of tool material and percentage share of the four main destructive mechanisms. Obtained results indicate the validity of employing ANN-based IT tools to build decision-support systems for the purpose of analyzing and forecasting the durability of forging tools.
EN
This article aims to depict the fundamentals of passage planning and route management for an autonomous vessels (AV). It presents a derivation of such a voyage passage plan, its step-by-step analysis, and a comparison to its conventional equivalent. This passage plan consists of four major parts: dock and harbour, en route, approach, and mooring stages. The whole activity of passage planning itself may be divided into the following stages: appraisal, planning, execution, and monitoring. The paper concludes with an overview of potential future applications and use of mentioned content.
EN
The purpose of this study is twofold: first, it is aimed at determining the architecture, energy balance of the system and the operational logic of the requests for energy use. Second, a defining a methodology that can help energy planners in the choice of the more appropriate alternatives of hybrid renewable energy system. Based on energy balance and operational logic within HRESs is proposed to conduct optimization research within socio-economic and energy efficiency scenarios. This research is proposed to use within DSS that can support the decision makers in selecting criteria, alternatives and trade-offs, thus making the energy planning simple. The methodology is divided in 3 steps: The selection of system structure in general, the determination of parameters of the system elements in all possible variants, and finally the estimation of efficiency and choosing the optimal variant of the system. For each alternatives is calculated the utility function within scenarios.
PL
Opracowanie dotyczy zastosowania programowania liniowego całkowitoliczbowego w optymalizacji wielokryterialnej. Celem badań było opracowanie modelu sterownika decyzyjnego umożliwiającego jednoczesną minimalizację poziomu zapasów półfabrykatów wygenerowanych w procesie cięcia, jak i odpadów po rozkroju. Zadaniem sterownika było dobranie odpowiedniego programu rozkroju z uwzględnieniem zamówień produkcyjnych, bieżących zapasów półfabrykatów i ograniczeń odnośnie dopuszczalnych poziomów zapasów.
EN
This paper concerns the use of integer linear programming in a multi-criteria optimization. The aim of the research was to develop a model of the decision support system allowing simultaneous minimization of the intermediate products stocks level and waste generated in the process of cutting. The goal of controller was to select the appropriate cutting program, including production orders, the current inventory and limits on permissible stocks levels.
PL
W pracy przedstawiono wyniki badań, dotyczące, procentowego udziału mechanizmów niszczących dla dwóch typowych wariantów eksploatacji narzędzi kuźniczych: smarowanych i chłodzonych oraz bez smarowania. Prezentowane wyniki pochodzą z opracowanego przez autorów systemu wspomagania decyzji (SEPEK-2) działającego w oparciu o sztuczną sieć neuronową. Wiedza o analizowanym zagadnieniu trwałości narzędzi kuźniczych, potrzebna do procesu uczenia sztucznej sieci neuronowej zawarta była w zestawie danych uczących, pochodzących z kompleksowych badań, zrealizowanych w warunkach przemysłowych. Zestaw danych uczących obejmował zbiór 450 rekordów wiedzy. W pracy przestawiono proces pozyskiwania wiedzy, przyjętą architekturę sieci neuronowej oraz parametry opracowanej sieci. Przeprowadzona globalna analiza wyników generowanych przez opracowany system, dla trwałości traktowanej jako zwiększająca się liczba odkuwek (od 0 do 25000 sztuk), wykazała że dla narzędzi smarowanych i chłodzonych dominującym mechanizmem jest zmęczenie cieplno-mechaniczne, a nie zużycie ścierne, które rzeczywiście dominuje w procesach kucia dla narzędzi niechłodzonych i niesmarowanych. Należy podkreślić, że zdecydowana większość opracowań z tego obszaru przypisuje, że to zużycie ścierne jest dominujące, a jak wykazały wyniki badań i analiz dla wybranych reprezentatywnych procesów kucia, przy wykorzystaniu systemu wspomagania decyzji opartego o SNN, to zmęczenie cieplno-mechaniczne jest dominujące w tych procesach. Jednakże ze względu na łatwą mierzalność oraz popularnie stosowane modele zużycia ściernego, bazujące na modelu Archarda, to właśnie zużyciu ściernemu przypisuję się największy udział, choć w rzeczywistości dla narzędzi smarowanych i chłodzonych zmęczenie cieplno-mechaniczne wzmaga ów efekt przypisywany zużyciu ściernemu. Natomiast ogólnie przyjęty pogląd jest słuszny, w przypadku narzędzi niesmarowanych. co potwierdziły także analizy przy wykorzystaniu SNN.
EN
The paper presents the results of research concerning the percentage participation of destructive mechanisms for two typical variants of exploitation of forging tools: lubricated and cooled, and without lubrication. Discussed results come from the developed by the authors the decision support system (SEPEK-2) based on artificial neural network. The knowledge about the durability of forging tools needed for learning artificial neural network was included in the training data set, from comprehensive studies, carried out in industrial conditions. Set of training data set included 450 records of knowledge. The paper presents the process of acquiring knowledge, adopted neural network architecture and parameters developed network. Carried out a global analysis of the results generated by the developed system for the durability of forging tools treated as the maximum number of produced forgings to their destruction (from 0 to 25,000 items), showed that for the lubricated and cooling tools the dominant mechanism is thermo-mechanical fatigue, and do not abrasive wear, which actually dominates in the process of forging tools for uncooled and unlubricated tools. It should be emphasized that the overwhelming majority of studies in this area is attributed that to abrasive wear is dominant, and as shown by the results of research and analysis for the selected representative forging processes, with the use of decision support system based on ANN, the fatigue a thermo-mechanical is dominant in these processes. However, due to the easy measurability and commonly used models wear, based on the model of Archard, it is abrasive wear assigned the largest participation. In fact, for the tool lubricated and cooled tools a thermo-mechanical fatigue intensifies this effect attributed to abrasive wear. While the generally accepted view is correct, in the case of tools unlubricated, as confirmed by the analysis using ANN.
EN
This paper proposes ways of personalization the process of analysis and management of financial flows of the company that provide definition of strategy for business development. In order to ensure the individual approach have been analyzed the methods of optimization of for making strategic decisions and have been identified peculiarities of their application in this area. This allowed to determine several measures to provide for dynamic changes that occur in the financial condition of the company under the influence of implemented solutions and select the most appropriate decisions to change strategy. For successful implementation, the search of strategy should to provide an individual approach to determining the quality of finances management by taking into account the personal data of activity the company. The modern concept of use of computers and information technology and implementation the expert knowledge provides for the creation of intelligent information systems in specific subject areas: management, audit, statistics etc. Therefore, for solving the basic problems is proposed development of intellectual information system of financial management, which will offer the user optimal options, making for strategy development through intellectual component. As the prototype of such a system is the intelligent information system of financial management (IISFM) that is characterized by a set of informational, technical, programmatic and technological means of telecommunication, knowledge bases and data banks, methods and procedures.
18
Content available Implementation of Anti-collision System on M/F WAWEL
EN
The known navigational systems in use and methods of navigational decision support perform information functions and as such are helpful in the process of safe conduct of a vessel. However, none of these known systems provides a navigator with ready solutions of collision situations taking account of all the vessels in the proximity of own ship, where the Collision Regulations apply. This paper presents verification results of NAVDEC - new Navigational Decision Supporting System created by research team from Szczecin Maritime University both for ocean going ships and pleasure crafts. Verification was carried out in real condition on board Motor Ferry ‘Wawel’ (m/f ‘Wawel’), which belongs to shipowner Polferries (PŻB). During the journey to/from Nynashamn system was tested from customer perspective. Few suggestions for improvements were issued, which were discussed in this article.
PL
Znane nawigacyjne systemy i metody nawigacyjnego wspomagania decyzji pełnią funkcje informacyjne i bez wątpienia są pomocne w procesie bezpiecznego prowadzenia statku. Żadne z tych rozwiązań nie dostarcza jednak nawigatorowi gotowych rozwiązań sytuacji kolizyjnej z uwzględnieniem prawideł unikania kolizji jednocześnie wobec wielu jednostek będących w pobliżu. W artykule przedstawiono wyniki weryfikacji poprawności działania systemu NAVDEC - nowego systemu wspomagania decyzji nawigacyjnych opracowanego w Akademii Morskiej w Szczecinie z myślą zarówno o statkach pełnomorskich, jak i rekreacyjnych. Weryfikację wykonano w warunkach rzeczywistych na pokładzie promu m/f „Wawel” należącego do Polferries na trasie do Nynashamn i z powrotem pod kątem oczekiwań użytkownika. W wyniku testów zaproponowano pewne ulepszenia, które przedstawiono w artykule.
EN
The paper presents a concept of the new algorithm solving Last Moment Manoeuvre problem. Last Moment Manoeuvre means that action taken only by one vessel is not enough to avoid collision. This is why both vessels have to synchronize their manoeuvres to pass each other. The main focus of the proposed solution is concentrated on the procedure defining the best possible manoeuvre for each vessel when avoiding a collision is no longer possible. For simplification, the assumption that the parameters of the vessels involved in the Last Moment Manoeuvre meet Standards for Ships Manoeuvrability set out in the IMO resolution, will be adopted. The algorithm presented in the paper will be implemented and tested in the commercial system.
PL
W artykule przedstawiono nowy algorytm rozwiązania, tzw. manewru ostatniej chwili. Pod tym pojęciem autorzy rozumieją manewr, gdy działania podjęte przez tylko jeden statek nie zapewnią uniknięcia kolizji. Dlatego oba statki muszą zsynchronizować swoje manewry, by minąć się bezpiecznie. Istota zaproponowanego rozwiązania sprowadza się do procedury definiującej optymalny manewr dla każdego statku, zapewniając jednocze-śnie zapobieżenie kolizji. Dla uproszczenia przyjęto założenie, że jednostki spełniają standardy dla sterowności statków ustanowione w rezolucji IMO. Zaproponowany algorytm będzie implementowany i przetestowany w systemie oferowanym komercyjnie.
EN
The target of this paper is to present the preliminary concept of decision support system for seaports supply chain risk management in the aspect of vulnerability and resilience engineering. As a result, there is discussed a literature review connected with resilience engineering of seaport infrastructure systems and their supply chains. Later, the decision support system conception is investigated. The developed solution is to be based on the What if? approach and Bow-Tie method. The work ends up with summary and directions for further research.
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