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Let Silent Big Data Wing Artificial Intelligence
Operational research can make AI "learn" from the current solution of specific problems to solve a variety of typed problems - let silent big data into the wings of AI. Widely used artificial intelligence, cool black technology, recently closed in Chongqing International Intelligent Industry Expo, the latest intelligent research products dazzling. And a scientific research team of Chongqing Normal University is following the latest developments of the intelligent industry here, integrating operations research and artificial intelligence, and carrying out practical exploration of interdisciplinary subjects. With big data and artificial intelligence becoming new directions of development, Professor Yang Xinmin of Chongqing Normal University and his team, as a scholar in the field of basic science, have realized that relevant basic research must keep up with them in time since a year ago. "Mathematical modeling and algorithms are the specialties of operations research." Yang Xinmin said that operational research can optimize the universality of AI problem solving, that is to say, it can make AI "learn" from the current solution of specific problems to solve a variety of typed problems. "Major decisions cannot be made by feeling. They must be made clear by data." Yang Xinmin told reporters that operations research can not only be applied to government decision-making, but also play a role in daily life. For example, the shortest path between two locations and the best portfolio of securities investment can be optimized by mathematical modeling. In other words, silent big data can give artificial intelligence wings to take off.
Help your life
More than 2,000 years ago, Sima Qian, a historian of the Western Han Dynasty, wrote the famous phrase "in the stratagem of a man, he will win a thousand miles away", praising Zhang Liang, a famous Minister of the Western Han Dynasty, for his military brilliance and good command.
In the early 1930s, a mathematical discipline named operations research emerged. It uses statistics, mathematical models and algorithms to find the best or approximate best solutions to complex problems through large data.
Yang Xinmin has devoted more than 30 years to the study of operational research, solving the academic problems that have plagued him for many years. He has also given more attention to China's operational research worldwide and provided many basic theoretical studies for the use of large data today.
Most people think that the big data is rather boring, but in Yang Xinmin's eyes it is very attractive. Operational research, he said, is not only theoretical knowledge, but also a solution to complex problems in reality. Whether in the past, now or in the future, it can help human life.
Yang Xinmin told reporters that operations research is a discipline that abstracts complex problems into mathematical models and then uses mathematical theory to find the optimal solution. This means that operations research not only has rigorous, pure and elegant mathematical charm, but also has a very convincing reference decision-making function. It is this characteristic that deeply attracts Yang Xinmin, and also shows him the bright prospect of applying what he learns to practice.
Today, the "Operational Research and Cybernetics" Laboratory of Chongqing Normal University led by Yang Xinmin is the only Key Laboratory of the Ministry of Education in the field of mathematics in Southwest China. The construction of mathematics discipline of Chongqing Normal University also relies on operational research to form a "point-to-surface integration" trend, and is in the forefront of universities in the country. Let silent data "speak up"
"Operational research was born during World War II, and it originated from the Allied forces'research on how to deploy military materials more efficiently." Yang Xinmin said that operational research had the function of solving complex problems naturally at the beginning of its publication. It can make a lot of silent raw data "speak up" and provide a clear scientific basis for major decisions. As early as the end of the 1980s, Professor Yang Xinmin began to devote himself to original research in many directions in the field of operational research, and solved several difficult problems in the field of international operational research successively, including the open problem of vector scaling raised by Academician Wang Shouyang, the denominator function problem in the multi-objective optimization problem that has puzzled the operational research circle for many years, and so on. It has been widely recognized at home and abroad and cited by scholars of relevant international research institutions.
Although remarkable achievements have been made in theoretical research, Yang Xinmin is by no means "deaf to the outside world". While studying operational research theory, he also cares about the practical application of basic theory. In the early 1990s, Professor Yang Xinmin cooperated with another scholar to complete the topic of "Chongqing Industrial Policy Research" by government departments, and to explore which industries should be developed as the pillar industries of Chongqing. What can objectively reflect the development of various industries in Chongqing is the data recorded on paper. Professor Yang told reporters that computers were not popular at that time, and a large number of raw data were recorded on paper documents. With the students, he manually input the original data of two cars into the computer, and then made statistics, modeling and analysis. After that, he drew the conclusion that automobile, motorcycle, machinery and other industries should be the pillar industries, and obtained the decision-making approval of the municipal government, which greatly promoted the development of local economy.
Explore the integration and development between the two In Yang Xinmin's view, operations research has a great relationship with large data intelligence. "We are exploring the combination of operations research and artificial intelligence. In fact, they have already been combined. For example, we say statistics is the basis of big data, while operations research is technology and can optimize algorithms." Previously, Yang Xinmin was very interested in the AI "Alpha Dog" game developed by Google. Through continuous attention, he found that the mathematical modeling and algorithm of "Alpha Dog" based on massive chess score is the key to its success.
To this end, in the summer of 2017, Yang Xinmin and his team collectively "make-up lessons" big data, artificial intelligence theory. In the first half of this year, under his suggestion, the School of Mathematics of Chongqing Normal University selected 50 students to carry out a pilot project, adding large data and AI related content to their curriculum, with the aim of training applied mathematics talents with practical ability in the field of big data and AI. "Although there are no systematic textbooks at present, our students are learning the basic knowledge of machine learning, in-depth learning, neural network and so on. Their textbooks are Monographs on these aspects." He said.
In order to make up for the shortage of talents related to AI in big data, Yang Xinmin recently put forward some suggestions on the training of talents specializing in big data and AI. He hoped to organize experts to compile relevant textbooks, train university teachers and add courses of big data and AI to college students majoring in mathematics and computer. (Source: People's Daily)