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Today, with the rapid development of science and technology, knowledge and wisdom play greater roles and the evolution of artifacts is faster. The speed of artificial evolution cannot be followed by natural evolution. As a kind of new intelligent information processing technology, granular computing enjoys widespread concern of scholars. The constant integration of biological evolution, artificial life and calculation method has also been a hot research topic among scholars. The main findings of this paper include the following four parts: propose Rough set model based on granular computing; propose knowledge discovery algorithm based on granular computing; propose new project modeling method based on granular computing; propose Artificial Selection Algorithm (ASA) based on granular computing. This paper unifies the existing classic Rough set model, Rough set model based on probability and Rough set model based on inclusion degree all on the Rough set model based on granular computing. Introduction As can be seen from the development history of science, science was a unified system when it was in its infancy in the ancient civilization. From the late 19th century to early 20th century, science entered into a period of modern development with physics evolution as the beginning. With new ideas, new technologies and new means, people marched along with different levels of the material world, leading to the birth of emerging disciplines, inter-disciplines and integrated disciplines, and meanwhile, providing new fields, new angles and new ideas for scientific research. In the 20th century, genetics, gene theory and DNA double helix model were established, molecular biology was generated, and unprecedented achievements had been made in modern chemistry, biology, astronomy, cosmology and life science. The rise of information theory, cybernetics and system theory as well as the generation of self-organizing system theory provided a broader space for development of modern technology revolution. The 20th century became the era of atomic energy, the era of aerospace and the era of electronic technology and computer. As time goes on, people gradually realize the importance of knowledge. The improvement of basic genetic algorithm is promoted to the improvement of natural evolution process based on knowledge. However, people’s subjective initiative and data information produced in the evolution process have not been fully used. The role of humans in the evolutionary algorithm is small and passive. As a classic and widely used evolutionary computation method, the genetic algorithm (GA) simulates the evolution law of “natural selection and survival of the fittest” in the natural evolution, 3rd International Conference on Management, Education, Information and Control (MEICI 2015) © 2015. The authors Published by Atlantis Press 672 ignores the dynamic information accumulated in the evolution information, and completely separates itself from man-made interference in evolution. Though this interference is beneficial sometimes, it is the advantage of GA and also the defect of GA. Some scholars analyzed the mode, but the analysis was not sufficient. From another perspective, the evolution process of GA is actually the process of knowledge production and accumulation. GA produces a large amount of knowledge in the evolution process. These data contains knowledge produced by the system in the evolution process. GA evaluates candidate solutions with fitness function, selects outstanding individuals in a random and probable mode, and approaches the optimal solution at a natural angle, but it does not clearly use the knowledge produced and accumulated by itself in the whole process. Therefore, a method of knowledge discovery can be adopted to dig out the original data. By reducing the dimensionality of data and complexity of data, the data is summarized, abstracted, refined and distinguished. Human wisdom is used and human requirements are considered to guide the evolution of GA. According to this idea and based on standard GA, this paper introduces the concept of ASA. As for the research method, a new and effective tool granular computing idea for knowledge discovery and knowledge processing and the knowledge discovery method based on granular computing are used to dig out knowledge and refine law from data in the evolution process, exert the discovered knowledge in the evolutionary information system and simulate artificial selection process to lead evolution direction. Therefore, this paper focuses on description of granular computing, knowledge discovery algorithm based on granular computing and artificial selection algorithm based on granular computing. Philosophical Foundation of Artificial Selection Algorithm Since Ludwig von Bertalanffy founded the system theory, the development of this theory has been extremely rapid, showing its powerful vitality in application field. Meanwhile, the system perspective and system method it proposes has risen to the system philosophy. The research object involved can be discussed and studied as a system to find out the inner certain relationship and reveal the general law, thus achieving the objective of recognizing and modifying the world. Therefore, the system theory is both outlook on world and methodology and has general applicability. Marxism philosophy is the science about the most general laws of development of nature, society and human thinking. It focuses on study of scientific methodology, including the research on general method and specific method of natural science. The main methodologies include the outlook on nature and natural law of trinity of material, movement, space and time; scientific experiments and dialectical thinking; analysis and synthesis: hypothesis and proof. Obviously, natural science methodology is a combination point of natural sciences and philosophy. Dialectical materialism holds that the world is material, the material is in motion, the motion is regular, and the law can be observed, used, recognized and mastered. By understanding and mastering the law of things, we can solve all kinds of problems better. We advocate combination of materialism and humanism because: our philosophy includes both ontology and creation; human creativity should start from objective reality and respect the objective laws. In any case, the matter is of great significance for human survival and development. We hope to achieve the unity of human and matter in the premise of people orientation.

Theoretical Research on Granular Computing and Artificial Selection Algorithm