Nowadays, there are developed countries economically and politically powerful. The most recognized worldwide are United States and China. Even though these two countries have a very strong economic, they are different and similar in several ways.
Social structure in China is formal and hierarchical. Chinese know where they fit in the structure and they abide by the rules there. There is no crossing into other areas. However, in the United States, it is much more loose and informal. It is not uncommon to see people of different social classes talking to each other and socializing. There are only few lines that socially are not allowed to be crossed.
Chinese society places high values on the morals of their people. They mostly don’t get marry until the late twenties. In fact, dating is not allowed in young people’s lives. The American culture is more relaxed and some could even argue that there needs to be more moral emphasize. Teens leave their parents’ house by age of 18, and most start dating when they are in Middle School.
Chinese love socialization in their business. Business becomes secondary as the parties get to know each better. If it delays a contract, that is perfectly acceptable as long as the correct social time is allotted for. In America, business associates are usually more aloof. There might be some social gathering, but the business is more important and the socializing will be sacrificed to get the job done if needed. Although there seems to be shift in America regarding this, the recognition of networking is becoming more popular.
When doing business in China, be prepared for much socializing. Business becomes secondary as the parties get to know each better. It does not mare if a contract is delay as long as they are meeting their new partner. In America, business associates are usually more apart. There might be some social meetings, but the business is more important than socializing. Socializing for Americans is always sacrificed to get the job done. Though there seems to be shift in America regarding this. The recognition of networking is becoming more pronounced.
In conclusion, these different do not make these countries better or worst. On the contrary, they make them unique. The United States and China are both monsters in the economics of the world. These different are own of their traditions and cultures.


Nowadays, Uncertainty and vogues problems become an important issue in generating fuzzy rules from numerical data. To handle uncertainty, vagueness and imprecision problems, it is important to develop intelligent and efficient systems. Generating appropriate fuzzy rules is one of the most challenging issues in fuzzy systems’ design. Thus, there is a need for using meta-heuristic search mechanism to generate membership function automatically. The success of developing a paramount fuzzy profile and the fuzzy rule base relies on using an efficient membership function and fuzzy rule base. 1On the other hand, planning the infrastructure of a typical Telecommunication Access Network (TAN) is a challenging problem due to the implied high level of both uncertainty and ambiguity. Otherwise, Building or designing a set of fuzzy rules depends on the accuracy of human being’s knowledge or experience, which based on the existing planning regions.
Membership function and fuzzy rules 2 play a very important role in making a fuzzy decision about determining the location of the Multi Services Access Node (MSAN), which considered as the new solution and recent technology for fixed telecommunication services is a complex problem based on many barriers and obstacles.
In many developing countries, MSAN becomes an important technology which meets an enormous demand for new business and residential telephone service. But, there are many obstacles in determining the best location of MSAN such as, continuous increasing of a number of subscribers which makes determining the best location of MSAN with high accuracy very difficult. So, thus, effects on the grade of service. As well as, MSAN’s providing service wants to satisfy the needs of thousands of new subscribers with high-quality telephone service and supply the right equipment, at the right place, and at the right time to reach an acceptable grade of service with a minimum number of MSANs. 3
This paper presents a new model of ABCMax-MinFitCorr for classifying the MSAN’s planning rules. The seven MSAN’s features (barriers) are used for classifying two classes of MSAN installation decisions where the membership degrees of each MSAN’s features (barriers) will used as input. The presented ABCMax-MinFitCorr model combined the Artificial Bee Colony capabilities using correlation function as a fitness function and the mamdani inference system to select appropriate rules with respect to the training data. The classification results are used for evaluating the ABCMax-MinFitCorr. The total classification accuracy of the ABCMax-MinFitCorr model was 98.68%. We therefore have concluded that the proposed ABCMax-MinFitCorr model can be used in classifying the MSAN’s features (barriers) by taking into consideration the misclassification rates.

This paper tries to build fuzzy rules in three stages: the first stage generates automatic membership function parameters using a meta-heuristic search mechanism and the information theory measures as the fitness function to adjust particles using Particle Swarm Optimization with Total Entropy (PSO-TE). In the second stage, the result of the first stage is delivered to proposed hybrid model by using Artificial Bee Colony with correlation function (ABCMax-MINFitCorr) as a fitness function to select appropriate rules with respect to the training data. The final stage in this research will introduce the test data which will be used to check for the accuracy of the whole system.

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