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The urban ecosystem is a complex system hat are compounded of environment -economic-social ,the factors of urban ecosystem affect the decision of the floating population to chose city .In this paper ,we according to the urban ecosystem to design the questionnaire ,and study the weights of the factors that influence the decision by AHP ,and find that economy is most important which is 0.6806, the society and ecological environment are 0.2014and0.1180.

The system of Case Based Reason is researched in this paper, a kind of genetic algorithm is proposed to solve the problem of feature vector space, and proposes an approach of integration of CBR AND RBR, an example about fish disease diagnose inferring integration model is given.

Information technology acceptance has received much attention, but little research has been conducted to assess farmers’ information adoption. Despite the importance of information, its value will not be realized if farmers are reluctant to accept it. This research aims to study farmers’ information adoption in China, in order to provide some decision-making advice for the people and organization who supply the agriculture information. The model of information usage intention has been established based on the Technology Acceptance Model (TAM). A sample of 231 farmers participated in this study. The results show that the factors which influence the usage willingness for information are perceived usefulness, perceived ease of use, learning intention, risk preference and experience in information before. In addition, income and education may also affect the decision.

Dissolved oxygen (DO) concentration plays a very important role in fish life and aquaculture, but DO prediction is very difficult. So a decision support system for DO prediction based on fuzzy model and neural network was attempted. The paper was based on vast monitored data, every day detecting for two years, in aquaculture pond in North China for two years. This is a preliminary attempt towards a wider use of Artificial Neural Networks in the management of aquaculture water quality. It proposes a model to be used effectively in prediction of DO concentration in aquaculture. This is really a crucial task, especially during the long dry summer months. The prediction of potential risk due to low DO is also very important. This data volume was divided in the training subset comprising of 106 cases and in the testing subset containing 26 cases. The input parameters are sunlight, wind speed, temperature, water temperature, air pressure, pH value and NH-NH3. Consequently three structural and seven dynamic factors are considered. After several and extended training-testing efforts a Modular Artificial Neural Network was determined to be the optimal one.

Fresh fruits and vegetables has become a public concern from the food security aspect. And the prediction of shelf-life loss under the fluctuated temperature becomes one of the key problems in food supply chain operation. So this paper identifies the impact aspects of produce decaying during distribution. For the key temperature factor, the process is divided into three phases: sorting, traveling and door-opening. Based on time-temperature function, a model of shelf-life loss of horticultural produce during distribution is developed by evaluating respiration rate of vegetables and fruits considering both the environment fluctuated temperature and vehicle vibration during traveling. Taking eggplant as an example, the numerical experiment result demonstrates that the average cost for ambient distribution is 2.8 times of the insulation way.

Water pollution is becoming the major factor damaging the sustainable development of aquaculture and the quality security of aquatic product in China. This paper introduces a decision support system for evaluating and managing quality risk contaminated by water pollution. The architecture, main components and their functions, especially a series of risk evaluation methods and models are described. At present, the system is in pilot in the city of Beijing in China. The stage achievements in developing the system are summarized.

Although effective implementation of the Internet technologies has a great potential for improving efficiency and reducing wastage within the fresh produce supply chain. the situation of the Internet usage by SMEs (small and medium sized enterprises) in the fresh produce supply chain is still unclear in China. As the main players, SMEs haven't been given enough attention from both academics and governments. Therefore, this research attempts to address this issue by, first, investigating the current usage of the Internet and related software by Chinese SMEs in the fresh produce supply chain, and then, by identifying enablers and barriers faced by SMEs to call government's attention. As a part of an EU-Asia IT&C funded project, a survey was carried out with SMEs in this industry from five major cities in China. The results reveal that in the relatively developed areas of China, SMEs in the fresh produce supply chain are rapidly adopting the Internet and software packages, but the level of adoption varies greatly and there is a significant lack of integration among the supply chain partners. Chinese SMEs are keen to embrace emerging technologies and have acted to adopt new software and tools. Given that cost of implementation is not a barrier, their concern over legal protection and online security must be addressed for further development.

In this paper, genetic algorithms and machine learning theory and method of knowledge acquisition for expert system structure is proposed to solve the "bottleneck" problems in the traditional machine learning methods on the basis of AQ, the model of knowledge acquisition based on GA is proposed and its application is used in the Fish Disease Diagnosis reasoning system, the rules is accessed to fish disease diagnosis. Fish Disease Diagnosis and the problems of knowledge accessed into combinatorial optimization are solved.

As China's meat production is growing, the quality safety of meat food as an important human food sources has increasingly become a major issue which related to the national economy and people's livelihood. Using early warning technique, tracking and tracing techniques and so on in the key link of meat food production in order to fulfill quality control is an important method which can effectively guarantee the food quality and safety. The use of RFID techniques and handhelds can automatically collect information about sheep breeding. Meanwhile this information could be inquired conveniently through Internet. This study uses C/S (Client/Server) model structure, and builds the sheep breeding traceability system based on RFID.

A method to express Profile Hidden Markov Model (Profile HMM) parameters with compressing matrix is presented, which is obtained by imposing the characteristics of both the state transfer and the character output in the Profile HMM. Profile HMM, Multiple sequence alignment, Bioinformatics

With the recent rapid progress of computer technology, researchers have attempted to adopt artificial intelligence and computer networks to develop computer-aided tutoring systems. Meanwhile, some have also attempted to develop more effective programs to test and enhance the learning performance of students. This study surveyed the current theoretical basis and design principle and proposed a web-based knowledge aided tutoring system for vegetable supply chain. The main idea of this paper was focused on the interactive design and feedback control. The proposed concept was illustrated by the functions of chat system, discussion section, questionnaires and online learning record, etc.

The fishing industry not only acts as foreign exchange earner but also plays an important role in China’s economy. But with the development of technology and liberalization of international trade, the foreign countries adopted in succession trade barriers to limit China’s fishery product export, which had make China’s fishery product export disproportionated with fishery products production. By the literature analysis, we find practical research aiming at aquatic products export trade is in shortage greatly. So it is necessary to provide risk management for export trade of aquatic products. A decision support system for risk management in aquatic products export trade had been developed by China Agricultural University. Based on questionnaire and interviews, we analyze the decision problems, user needs and the difficulties involved in developing the aquatic products risk management system. The system architecture and its components, such as database, knowledge base and model base are described. At last we discussed on problems we had encountered during development and promotion.

Fish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able to access the Internet. Telephone and mobile uses increase rapidly, so, the provision of call centre service appears as a sound alternative support channel for farmer to acquire counseling and support. This paper presents a research attempt to develop and evaluate a call center oriented Hybrid disease diagnosis & consulting system (H-Vet) in aquaculture in China. This paper looks at why H-Vet is needed and what are the advantages and difficulties in the developing and using such a system. A machine learning approach is adopted, which helps to acquire knowledge when enhancing expert systems with the user information collected through call center. This paper also proposes a fuzzy Group Support Systems (GSS) framework for acquiring knowledge from individual expert and aggregating knowledge into workgroup knowledge by H-Vet in the situation of difficult disease diagnosis. The system’s architecture and components are described.

There are three kinds of uncertainty in the process of fish-disease diagnosis, such as randomicity, fuzzy and imperfection, which affect the veracity of fish-disease diagnostic conclusion. So, it is important to construct a fish-disease diagnostic model to effectively deal with these uncertainty knowledge's representation and reasoning. In this paper, the well-developed parsimonious covering theory capable of handling randomicity knowledge is extended. A fuzzy inference model capable of handling fuzzy knowledge is proposed, and the corresponding algorithms based the sequence of obtaining manifestations are provided to express imperfection knowledge. In the last, the model is proved to be effective and practicality through a set of fish-disease diagnostic cases.