Bayesian methods in reliability of search and rescue action

Burciu, Zbigniew

doi:10.2478/v10012-010-0039-7

Cited by 8 publications

(5 citation statements)

References 2 publications

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“…For the purpose of supporting the planning and monitoring of rescue operations at sea, a Bayesian network application method is proposed by [5]. For this purpose, the principles for determining the reliability of the raft are presented.…”

Section: Literature Overview (State Of the Art)mentioning

confidence: 99%

Fuzzy Logic in Selection of Maritime Search and Rescue Units

Małyszko

2021

Applied Sciences

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The article discusses methods of ships assessment when determining their suitability for search and rescue action (SAR) at sea. Selection of the most preferable ships is one of the action planning elements. Due to various construction and equipment the civilian ships can only perform rescue task to a certain degree. According to the Multi-Criteria Decision Analysis (MCDA), many parameters and data have to be compared in order to create a ranking of vessels ordered according to the coordinator’s preferences. When data are missing, incomplete or uncertain, a similar effect can be obtained using fuzzy logic. The author discussed the nature of the criteria, evaluation methods and presented a simulation of a ship study using fuzzy logic. The author developed fuzzy rules and presented the principle of operation of the controller. The article deals with the main principles of a decision support system (DSS) for the selection of ships in SAR operations.

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Section: Literature Overview (State Of the Art)mentioning

confidence: 99%

Fuzzy Logic in Selection of Maritime Search and Rescue Units

Małyszko

2021

Applied Sciences

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“…By solving the Lagrange equation, the displacement of each particle is determined and then the dynamic tracking of the particle is realized. Several formulas, such as that of the simplified search planning method (SSPM), mentioned in "Theory of Research: A Simplified Explanation" [23], the Bayesian method [24][25][26], and the Basic Probability Calculation Method, are generally used to calculate the POC. In fact, these methods are different.…”

Section: Description Of the Probability Of Containmentmentioning

confidence: 99%

A Decision-Making Algorithm for Maritime Search and Rescue Plan

Otote

et al. 2019

Sustainability

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With the development of the maritime economy, sea traffic is becoming more and more crowded, and sea accidents are also increasing. Research on maritime search and rescue decision-making technology cannot be delayed. This paper studies the maritime search and rescue decision algorithm, based on the optimal search theory. It also analyzes three important concepts: Probability of containment (POC), probability of detection (POD), and probability of success (POS) involved in the maritime search and rescue decision-making process. In this paper, the calculation methods of POC and POD variables have been improved, and the search success rate has been improved to some extent. Finally, an example analysis of the maritime search and rescue incident is given. Through verification, the algorithm proposed in this paper can support maritime search and rescue decisions.

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“…The probability of containment (POC) refers to the probability that the SAR target exists in a certain area, which is an important factor affecting the POS [23]. This article considers the POC as consisting of two parts.…”

Section: Mathematical Model In Search Theory a Probability Of Containmentmentioning

confidence: 99%

An Intelligent Decision Algorithm for the Generation of Maritime Search and Rescue Emergency Response Plans

Gao

et al. 2019

IEEE Access

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Maritime search and rescue (SAR) decisions are the most important part of maritime SAR operations. In the process of making maritime SAR decisions, a key factor affecting efficiency and success rate is how to quickly respond to accidents and develop an emergency response plan. At present, maritime SAR emergency response plans are still mostly obtained through a combination of drift prediction models and SAR experience. There is a lack of SAR resource scheduling and SAR task assignment. The primary purpose of this paper is to explore the possibility of using an intelligent decision-making algorithm to formulate maritime SAR emergency response plans so as to produce results more scientifically. First, the relevant research areas and research data are briefly introduced, and the main mathematical models involved in the optimal search theory are expounded. Next, key technologies involved in the process of maritime SAR emergency response plan generation, including the determination of search area, the scheduling of SAR resources, the allocation of search tasks, and the planning of search routes, are analyzed in detail. Two optimization model algorithms, namely the SAR resource scheduling model based on genetic simulated annealing algorithm (GSAA) and the regional task allocation algorithm based on space-time characteristics, are proposed as approaches to solving the problem of resource scheduling and task allocation. Finally, the effectiveness and optimization of the proposed algorithms are verified by analyzing the emergency response of a real case which occurred in the Bohai Sea and comparing the different schemes. Through the algorithm proposed in this paper, the efficiency of maritime SAR operations can be effectively improved and the loss of life and property can be reduced.

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Bayesian methods in reliability of search and rescue action

Abstract: ABSTRACT

Cited by 8 publications

References 2 publications

Fuzzy Logic in Selection of Maritime Search and Rescue Units

Fuzzy Logic in Selection of Maritime Search and Rescue Units

A Decision-Making Algorithm for Maritime Search and Rescue Plan

An Intelligent Decision Algorithm for the Generation of Maritime Search and Rescue Emergency Response Plans

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