Water quality assessment for Ulansuhai Lake using fuzzy clustering and pattern recognition

Water quality assessment of lakes is important to determine functional zones of water use.Considering the fuzziness during the partitioning process for lake water quality in an arid area,a multiplex model of fuzzy clustering with pattern recognition was developed by integrating transitive closure method,ISODATA algorithm in fuzzy clustering and fuzzy pattern recognition.The model was applied to partition the Ulansuhai Lake,a typical shallow lake in arid climate zone in the west part of Inner Mongolia,China and grade the condition of water quality divisions.The results showed that the partition well matched the real conditions of the lake,and the method has been proved accurate in the application.

Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China

Achieving water purity in Poyang Lake has become a major concern in recent years, thus appropriate evaluation of spatial and temporal water quality variations has become essential. Variations in 11 water quality parameters from 15 sampling sites in Poyang Lake were investigated from 2009 to 2012. An integrative fuzzy variable evaluation(IFVE) model based on fuzzy theory and variable weights was developed to measure variations in water quality. Results showed that: 1) only chlorophyll-a concentration and Secchi depth differed significantly among the 15 sampling sites(P < 0.01), whereas the 11 water quality parameters under investigation differed significantly throughout the seasons(P < 0.01). The annual variations of all water quality variables except for temperature, electrical conductivity, suspended solids and total phosphorus were considerable(P < 0.05). 2) The IFVE model was reasonable and flexible in evaluating water quality status and any possible ′bucket effect′. The model fully considered the influences of extremely poor indices on overall water quality. 3) A spatial analysis indicated that anthropogenic activities(particularly industrial sewage and dredging) and lake bed topography might directly affect water quality in Poyang Lake. Meanwhile, hydrological status and sewage discharged into the lake might be responsible for seasonal water quality variations.

QUALITY ASSESSMENT OF GINSENG BY CHEMICAL FUZZY PATTERN RECOGNITION

A new method of assessing ginseng and screening its bioactive constituents by fuzzy pattern recognition has been proposed.

Water Resource Pricing Study Based on Water Quality Fuzzy Evaluation: A Case Study of Hefei City

Price plays an important role in water resources management. The price of water resources can also be considered as a “water resource tax” which reflects the value and opportunity cost of water, and people will pay for the right to use water. Currently, the water resource fees’ effect of regulating resource differential revenues is not manifest and it’s not enough to reflect the principle of paid use of resources as well as regulating resources differential revenues. Due to the ambiguity and complexity of water resources price, this paper uses methods relating to fuzzy mathematics for modeling and processing. The study had a comprehensive consideration of five factors including water quality, water resources per capita, household consumption level, per capita GNP, population or population density to evaluate the water resource price.

Application of Fuzzy QFD to Aircraft Top Hierarchy Design

In this paper, based on the Quality Function Deployment ( QFD) method, theFuzzy Quality Function Deployment (FQFD) theory and the step-by-step hierarchy structure in aircrafttop decision design are studied. The fuzzy model for computing competitive factor in evaluation ispresented. The decision of key technologies for improving the performance and affordability of afixed-wing aircraft is studied using the model, and the result proves the feasibility of this model.

FUZZY REGRESSION MODEL TO PREDICT THE BEAD GEOMETRY IN THE ROBOTIC WELDING PROCESS

Recently, there has been a rapid development in computer technology, which has in turn led to develop the fully robotic welding system using artificial intelligence （AI） technology. However, the robotic welding system has not been achieved due to difficulties of the mathematical model and sensor technologies. The possibilities of the fuzzy regression method to predict the bead geometry, such as bead width, bead height, bead penetration and bead area in the robotic GMA （gas metal arc） welding process is presented. The approach, a well-known method to deal with the problems with a high degree of fuzziness, is used to build the relationship between four process variables and the four quality characteristics, respectively. Using these models, the proper prediction of the process variables for obtaining the optimal bead geometry can be determined.

FUZZY MODEL FOR TWO-DIMENSIONAL RIVER WATER QUALITY SIMULATION UNDER SUDDEN POLLUTANTS DISCHARGED

Based on the fuzziness and impreciseness of water environmental system, the fuzzy arithmetic was used to simulate the fuzzy and imprecise relations in modeling river water quality. By defining the parameters of water quality model as symmetrical triangular fuzzy numbers, a two-dimensional fuzzy water quality model for sudden pollutant discharge is established. From the fuzzy model, the pollutant concentrations, corresponding to the specified confidence level of a, can be obtained by means of the a-cut technique and arithmetic operations of triangular fuzzy numbers. Study results reveal that it is feasible in theory and reliable on calculation applying triangular fuzzy numbers to the simulation of river water quality.

Fuzzy finish time modeling for project scheduling

This research aims at developing a new fuzzy activity finish time estimation model for project scheduling management.With the application of the fuzzy quality function deployment (FQFD) and fuzzy analytic hierarchy process (FAHP) methods,the degree of fuzziness for every project activity is calculated in accordance with considerations of project uncertainties.These uncertainties are measured by the risk level of such project-related characteristics as time limit,activity start time,budget,manpower,technological difficulty,and facility requirements.In this paper,rather than applying the de-fuzzification technique to obtain the crisp activity duration for project scheduling,the fuzzy finish time estimation method for every activity is proposed based on the degree of fuzziness.The corresponding fuzzy activity duration time plot is also developed in a new fuzzy Gantt chart.The proposed model can provide a reasonable fuzzy finish time estimation for every activity,while most scheduling methods only provide the finish time of the entire project.Compared to existing models,this time estimation model and its corresponding Gantt chart are predicted to have higher reliability and practical application in project management and scheduling.

Combining Knowledge-and Data-Driven Fuzzy Approach to Evaluate Shelf-Life of Various Seafood Products

Due to the complexity of the deterioration process of seafood products,relying on one indicator is not adequate to determine the quality of such products.Usually,shelf-life was estimated based on various indicators complicating the decision-making process.Decision Support Systems are considered as a good solution.The current study aims to establish a simple and novel fuzzy model based on a combination of knowledge-and data-driven approaches to define a fuzzy quality deterioration index(FQDI)in various seafood products(rainbow trout,threadfin bream,and white shrimp samples)during cold storage.Total volatile basic nitrogen(TVB-N)and psychrotrophic microorganisms counts(PMCs)were determined based on traditional methods.The sensory analysis was performed by a data-driven fuzzy approach.Overall,the shelf-life of the rainbow trout fillet was estimated to be 8 d,based on all the freshness parameters.However,the shelf-life of the Japanese threadfin bream fillet was 5-7 d according to the microbial and chemical parameters,respectively.This time for shrimp samples was 6-8 d using sensory score and TVB-N contents.The results of data-driven fuzzy approach showed all of the quality properties were considered as the'Important'-'Very Important'(defuzzification score>75).The TVB-N and PMCs were the most and weakest freshness quality properties(defuzzified-values:84.64 and 78.75,respectively).Based on FQDI,the shelf-life of the rainbow trout,Japanese threadfin bream,and shrimp samples were estimated to be 8,5,and 7 d,respectively.This method was able to successfully provide a comprehensive deterioration index for evaluating the seafood shelf-life.Such a total index can be considered as a comprehensive output(y variable)to predict seafood freshness by rapid and nondestructive method.