Safe Ship’s Control in a Fuzzy Environment Using a Genetic Algorithm

2011 ◽  
Vol 180 ◽  
pp. 70-75 ◽  
Author(s):  
Mostefa Mohamed Seghir
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Decision Making Process ◽  
Fuzzy Environment ◽  
Ship Control ◽  
Marine Accidents

Marine accidents occurring nowadays testify to the fact that systems enhancing the level of navigational safety are indispensable. This paper describes a method of safe ship control in the collision situation in a fuzzy environment based on a genetic algorithm. The optimal safe ship trajectory in a collision situation is presented as multistage decision-making process. The results have been discussed.

scholarly journals The branch-and-bound method and genetic algorithm in avoidance of ships collisions in fuzzy environment

2012 ◽  
Vol 19 (Special) ◽  
pp. 45-49 ◽  
Author(s):  
Mostefa Mohamed-Seghir
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Branch And Bound ◽  
Decision Making Process ◽  
Branch And Bound Method ◽  
Continuous Observation ◽  
Collision System ◽  
Fuzzy Environment ◽  
Ship Control ◽  
Marine Navigation

ABSTRACT Marine navigation consists in continuous observation of the situation at sea, determination the anti-collision manoeuvre. So it necessary to determine ship safe trajectory as a sequence of ship course changing manoeuvres. Each manoeuvre is undertaken on the basis of information obtained from the anti-collision system ARPA. This paper describes a method of safe ship control in the collision situation in a fuzzy environment based on a branch and bound method and a genetic algorithm. The optimal safe ship trajectory in a collision situation is presented as multistage decision-making process

scholarly journals Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Lukas Falat ◽  
Dusan Marcek ◽  
Maria Durisova
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Decision Making ◽  
Soft Computing ◽  
Clustering Algorithm ◽  
Prediction Models ◽  
Moving Average ◽  
Series Data ◽  
Decision Making Process ◽  
Hybrid Neural Network

This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined withK-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

scholarly journals SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN POSISI PEMAIN IDEAL DALAM TIM SEPAK BOLA DENGAN METODE ALGORITMA GENETIKA

Compiler ◽  
2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Hizkia Alprianta ◽  
Anton Setiawan Honggowibowo ◽  
Yuliani Indrianingsih
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
User Interface ◽  
Interface Design ◽  
Selection Process ◽  
Decision Making Process ◽  
Media Processing ◽  
Ideal Position ◽  
The Right ◽  
The Ideal

So far, there are coaches who are less precise in determining the ideal position of the player as it only relies on instinct and the ego of the players so that there is still a coach who has not been able to objectively assess the players.By utilizing the method of Genetic Algorithm as Decision Support System (DSS) in the process of determining the ideal position of a player who uses several criteria (multicriteria) to choose a proper player. DSS is helping coach in making the right decisions and Genetic Algorithm is used as a model for multicriteria weighting in the selection process. This application was built with tools Borland Delphi (7.0) as the user interface design and media processing PostgreSQL as its database.            Based on these results we can conclude that this application expected to assist the coaches in the decision making process and can change the appraisal of which are subjective to more objective, to determine the ideal position for a player, can determine the best position of each position of a number of players and the expected results of the Genetic Algorithm on the system constructed in accordance with the results of manual calculations.

scholarly journals Comparison of Computational Intelligence Methods Based on Fuzzy Sets and Game Theory in the Synthesis of Safe Ship Control Based on Information from a Radar ARPA System

2019 ◽  
Vol 11 (1) ◽  
pp. 82 ◽  
Author(s):  
Józef Lisowski ◽  
Mostefa Mohamed-Seghir
Keyword(s):  
Decision Making ◽  
Optimization Design ◽  
Matrix Game ◽  
Advisory System ◽  
Control Optimization ◽  
Fuzzy Environment ◽  
Fuzzy Neural ◽  
Ship Control ◽  
Game Environment ◽  
Computational Intelligence Methods

This article presents safe ship control optimization design for navigator advisory system. Optimal safe ship control is presented as multistage decision-making in a fuzzy environment and as multistep decision-making in a game environment. The navigator’s subjective and the maneuvering parameters are taken under consideration in the model process. A computer simulation of fuzzy neural anticollision (FNAC) and matrix game anticollision (MGAC) algorithms was carried out on MATLAB software on an example of the real navigational situation of passing three encountered ships in the Skagerrak Strait, in good and restricted visibility at sea. The developed solution can be applied in decision-support systems on board a ship.

Decision Making in a Fuzzy Environment and its Management to the Diminishing Manufacturing Sources and Material Shortage Problems

2014 ◽  
Vol 513-517 ◽  
pp. 2672-2675
Author(s):  
Yuan Cheng Tsai ◽  
Yi Lun Chi
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Fuzzy Theory ◽  
Aerospace Industry ◽  
Possibility Theory ◽  
Lessons Learned ◽  
Fuzzy Environment ◽  
The Subject ◽  
Electronic Support

The paper formulated a proposed methodology to manage diminishing manufacturing sources and material shortage (DMS) with conclusions and recommendations on the subject of component obsolescence management in a military electronic support environment. By assessing applicable literature as well as feedback and lessons learned from relevant support projects, a strategy for the management of component obsolescence is proposed. The aim of the research is to explore the problem of managing DMS strategies by the method of project management and describes the risk of running distinct strategies to solve problems of DMS by fuzzy theory and possibility theory. Based on the results, this paper can be applied to support businesses quickly to determine the Strategies Combination, Resource Allocation and Inventory by using the model and genetic algorithm. A case study of an aerospace industry is used to illustrate the concept developed, which would be meaningful to reduce applicable obsolescence risks and thereby reducing related inventory and manpower costs.

scholarly journals Using genetic algorithm in dynamic model of speculative attack

Equilibrium ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. 287
Author(s):  
Bogna Gawrońska-Nowak ◽  
Wojciech Grabowski
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Dynamic Model ◽  
Information Structure ◽  
Foreign Exchange Market ◽  
Complex Nature ◽  
Decision Making Process ◽  
Currency Market ◽  
Speculative Attack ◽  
Nature Of Information

Evolution of speculative attack models shows certain progress in developing the idea of the role of expectations in the crisis mechanism. Obstfeld (1996) defines expectations as fully exogenous. Morris and Shin (1998) treat the expectations as endogenous (with respect to noise), not devoting too much attention to information structure of the foreign exchange market. Dynamic approach proposed by Angeletos, Hellwig and Pavan (2006) offers more sophisticated assumption about learning process. It tries to reflect time-variant and complex nature of information. However, this model ignores many important details like a Central Bank cost function. Genetic algorithm allows to avoid problems connected with incorporating information and expectations into agent decision-making process to an extent. There are some similarities between the evolution in Nature and currency market performance. In our paper an assumption about rational agent behaviour in the efficient market is criticised and we present our version of the dynamic model of a speculative attack, in which we use a genetic algorithm (GA) to define decision-making process of the currency market agents. The results of our simulation seem to be in line with the theory and intuition. An advantage of our model is that it reflects reality in a quite complex way, i.e. level of noise changes in time (decreasing), there are different states of fundamentals (with “more sensitive” upper part of the scale), the number of inflowing agents can be low or high (due to different globalization phases, different capital flow phases, different uncertainty levels).

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