Composition ship collision risk based on fuzzy theory

Despite of modern navigation devices, there are problems in navigation of vessels in waterways due to the geographical structures, disturbances in water, dynamic nature, and heavily environmental influenced sea traffic. Even though all vessels are equipped with modern navigation devices, the accidents are reported caused by various reasons and mainly by human factor according to investigation. We propose an effective and efficient composition collision risk calculation method for finding the collision probability and avoiding the collision between ships in possible collision situations. The proposed composition collision risk calculation method at ship's position using combination of fuzzy and fuzzy comprehensive evaluation methods. The algorithm is straightforward to implement and is shown to be effective in automatic ship handling for ships involved in complex navigation situations. Experiments are carried out with indigenous data and the results show the effectiveness of the proposed approach.

New Ranking of Generalized Quadrilateral Shape Fuzzy Number Using Centroid Technique

The output of the fuzzy set is reduced by one for the defuzzification procedure.It is employed to provide a comprehensible outcome from a fuzzy inference process.This page provides further information about the defuzzifica-tion approach for quadrilateral fuzzy numbers,which may be used to convert them into discrete values.Defuzzification demonstrates how useful fuzzy ranking systems can be.Our major purpose is to develop a new ranking method for gen-eralized quadrilateral fuzzy numbers.The primary objective of the research is to provide a novel approach to the accurate evaluation of various kinds of fuzzy inte-gers.Fuzzy ranking properties are examined.Using the counterexamples of Lee and Chen demonstrates the fallacy of the ranking technique.So,a new approach has been developed for dealing with fuzzy risk analysis,risk management,indus-trial engineering and optimization,medicine,and artificial intelligence problems:the generalized quadrilateral form fuzzy number utilizing centroid methodology.As you can see,the aforementioned scenarios are all amenable to the solution pro-vided by the generalized quadrilateral shape fuzzy number utilizing centroid methodology.It’s laid out in a straightforward manner that’s easy to grasp for everyone.The rating method is explained in detail,along with numerical exam-ples to illustrate it.Last but not least,stability evaluations clarify why the Gener-alized quadrilateral shape fuzzy number obtained by the centroid methodology outperforms other ranking methods.

On the Application of IPRA Tool in Risk Assessment and Management of International Construction Projects

Construction companies face threats from competition and must be able to adjust to modem technology and changes in customer expectations. These issues require efficient risk management techniques. The success of construction companies running projects in international markets depends on how the risks arise from the host country conditions as well as the project specific risk factors. Successful management of risks requires identification of risks, construction of a risk model which can be used to assess the magnitude of risks, and implementation of response strategies so that an acceptable risk-return balance can be achieved. The project success usually depends on the combination of all risks, response strategies used to mitigate risks, and a company＇s ability to manage them. There exists a need to develop risk models containing the risks of doing business in international markets and factors that affect manageability of these risks. One of the market＇s critical challenges is scheduled management and the understanding and application of program management. This paper uses systematic risk identification, classification and analysis, and measurement and response methodologies to help international contractors quantify the risks of project development and accomplishment.

Risk Assessment of Heavy Metal Pollution in Sediments of the Fenghe River by the Fuzzy Synthetic Evaluation Model and Multivariate Statistical Methods

Concentrations of heavy metals in 74 sediment samples from the Fenghe River, which originates from the north of the Qinling Mountains and flows through Xi'an, Shaanxi Province, China, were characterized by employing geographic information system(GIS)mapping, fuzzy synthetic assessment, and multivariate statistical analysis to determine the enrichment characteristics of heavy metals as well as their potential risks of pollution to sediments. Al, Cd, and Co were the major pollutants, with a high enrichment factor(EF) value. Heavy metal concentrations from samples near the paper plant were maintained at a high level. Significant enrichment of Al, Ba, Cr, Ni, Pb, and Co was found in the midstream and downstream, while high concentration of Cu occurred in the headwater stream. Based on the cluster and principal component analyses, sediment metals mainly came from the paper plants, agronomic practices, natural sources, and tourism, with a contribution of 51.59%, 23.01%, 14.21%, and 9.88%, respectively. Sediment pollution assessment explored using fuzzy theory based on the entropy method and toxicity coefficient showed that 26, 32, and 11 sites fell into Class III(slightly polluted), Class IV(moderately polluted), and Class V(heavily polluted), respectively, and their scores of membership degree in the polluted level were on the rise, suggesting a relatively high degree of sediment metal pollution in the study area. Closely related to the excessive industrial and agricultural applications, metal pollution in sediment is necessary to be addressed in the Fenghe River.