Research And Implementation For Maintenance Goal-Oriented Requirement Analysis Method

With the development of network, E-commerce and communicate technology, amounts of travel information resources become largely because of the rapid development of information society. So that when travelers face mass travel information they choose travel areas and travel routes very difficultly. As travelers become more sophisticated and rational concept of tourism, travel mode, the quality of tourism products, self-awareness and selectivity have changed. The fixed-information services which travel sites are provided can't meet the travelers' requirements. Therefore, travel information systems which travelers choose tourist attractions by themselves and dispose their travel time freely have become the focus of the study.To solve above problems, this paper based on goal analysis method will construct Mapping between the requirements and goals, classify goals and provide the target model and storage structure. Combining with the contents of this paper, according to the basic idea, basic principles and design methods of genetic algorithms design customer travel routes algorithm. It consists of two sub-algorithms:customer requirement goal acquisition algorithm and travel routes algorithm. First, according to the customer constraints as well as the relationship between maintenance goals and achievement goals, inquire goals in the database. Then generate customer travel plans.Using theories and methods of genetic algorithms and machine learning apply genertic algorithm thought to Self-learning of the knowledge base and provide a self-learning algorithm of goal base which can optimize the new travel goals and update goal base. Implement the design of database and travel routes using Java, Microsoft SQL Server 2000 database and other technologies. According to the characteristics of customers, design familiar, convenient and friendly personalized interface.Goal mode and Goal base structure in this paper well reflect customers' requirements. In the algorithms, operators and parameters of genetic algorithms can basically meet customer's needs. Friendly personalized interfaces enhance the customers'satisfaction with the platform.This paper is valuable for reference about tour plan recommending problem. And it also has strong meaning in practice. Of course, the genetic algorithm parameters also can improve and how to promote algorithm performance needs further study.