Research On Vehicle Cargo Matching In Logistics Platforms Based On Data Mining Methods

With the innovation of the market,the vehicle-cargo cooperation internet platform has basically met the actual question of the non-cooperation of information systems in high-speed transportation,and has greatly improvedtransport efficiency and industrial production group practice dimension analysis team management.Deep learning has become an important part of dimensional analysis of artificial intelligence technology and technical practice.We must visit these items individually.In particular,it focuses on dimensions that are rarely practiced and analyzes specific cases of real concern.This scientific research studies the above difficulties in deep science and analyzes the method of constructing the model by choosing the practical dimension.,intelligent solution and precise algorithm solution.The final research results are shown as follows:(1)Undergraduate scientific research focuses on multi-source combined transport in "multi-" vehicles according to the Empire,and further scientific research.We found that the Markov process has a certain difference,conducive to multi-directional scientific research and development and in detail according to the Empire to establish its current situation,action,marketing promotion,development and development strategy.According to the empire(2)By combining the two level understanding with RELU is according to the empire key parameters of our practice Enxi and the Adam algorithm developed is to simulate the whole development process of Q algorithm on the deep Internet,which is consistent with the perspective of Polomarkov’s practice of Enxi Empire and improvement.The algorithm uses the perspective Enxi hon language of Pyt practice and is implemented in PyCharm framework,which can effectively solve the problem of vehicle and cargo matching.