On December 16, Yuan Yaxiang, academician of the Chinese Academy of Sciences, member of the Standing Committee of the National Committee of the Chinese People's Political Consultative Conference, and vice chairman of the China Association for Science and Technology, was a guest in the lecture hall of the academician of science and technology innovation and gave a speech on "big data and optimization". He said that in the era of big data, a large amount of data is being generated in all aspects of production and life, but most of it has not been effectively used. Data optimization is to study the regularity, classification and quality of these data, and pick out the most optimal among a variety of choices.
Yaxiang Yuan is mainly engaged in the research of optimization calculation methods, and has made important contributions to the algorithm of nonlinear optimization, theory, trust domain method, quasi-Newtonian method and conjugate gradient method, and his research results are named "Yuan's lemma".
Starting from the "wide application of big data", Yuan Yaxiang introduced the important role of big data in the fields of transportation network construction, intelligent interactive Xi, health care, medical imaging, financial risk control, wireless communication, geological exploration and other fields.
For example, from a scientific point of view, the application of traffic data accounts for only a very small part of the total, but the people are already very rewarded.
For decision-making departments, data can help departments decide on bus routes, decide on the location of communities, primary schools, hospitals, etc. Autonomous driving is still in its infancy, and perhaps in 10 or 20 years, there will be more and more self-driving cars running on the streets.
Another wide application of big data is in medical treatment, before the people were most concerned about how to see a doctor, now more hope to be able to detect problems early, years of physical examination records can help find hidden dangers as soon as possible.
Finance is very widely used in big data technology, whether it is precision marketing, or risk control, etc., although there are mathematical formulas, stochastic differential equations, there is actually a large amount of big data behind it to make decisions.
In terms of wireless communication, big data plays a big role. Our country has taken a completely different path from the West in terms of epidemic prevention and control, because the use of big data has made it impossible for the West to do some of the things that China has done.
Agricultural modernization must pay attention to big data technology, including agricultural digital economy, smart agricultural product chain, and even breeding, planting, but also use big data to analyze, and then make scientific decisions. For rural cadres, big data can also provide good help for scientific decision-making.
Yuan Yaxiang believes that big data will play a very important role in various industries, and no matter what industry you are engaged in, the use of big data will improve value or efficiency.
Data processing consists of three aspects, namely statistics, calculations, and optimization. Yuan Yaxiang took data problems such as film evaluation, surveillance analysis and processing as examples, and introduced the optimization problems and main optimization algorithms that have attracted much attention in the world. As an important supporting technology to solve big data problems, optimization methods have been widely used in data science.
For example, protein folding in life sciences boils down to the optimization problem of minimal energy;In aerospace, the shape design of the aircraft, the selection of the spacecraft flight track, and the design of the payload layout all involve optimization problemsIn the fields of big data and artificial intelligence, the core of issues such as speech recognition, fingerprint recognition, and iris recognition can be boiled down to optimization problems. Road planning in autopilot and autonomous driving, whether it is the shortest path or the shortest time, can be boiled down to the optimization of graph and network flow.