Based on the logistics management and control system of the cold-rolled finished products, this system has realized many features, including three-dimensional positioning of the crane, a variety of real-time data collected through the RFID systems and magnet detection system and wireless data acquisition in the coil storage or out of the library or inverted treasury job process transmitted to the server, coil warehouse operations process optimization and control, forming automatically a plan and target location to crane, Prompting crane operations, real-time monitoring of crane operating, recording crane operating results, tracking and positioning of the treasury coil information, updating treasury stock coil position in real time, inquiry treasury stock and automatic generation of warehouse operations statements by teams or date or month or year, communication with ERP or MES etc. Through seamless connectivity between the crane operating system and warehouse management systems and enterprise information systems, the system can achieve precise synchronization of logistics and information flow.
This paper designed an implement scheme of the alnic automatic measuring system for rail type vehicles. The system can read information of rail type vehicles by adopting four alnics, through the PLC to achieve the vehicles’s direction measuring and vehicles counting and axle counting and velocity measuring. In order to improve system reliability, comprehensive application of the anti-jamming alnic, software fault-tolerant variety of anti-jamming measure. By setting the calibration alnic, the system effectively overcome the interference of a variety of human factors. By cleverly setting registers N1N1N3 and in accordance with the principle of FIFO N1N2N3 pass assignment, software design is simplified. This system is widely used in modern logistics production and transportation management process of large and medium-sized enterprises involving the train transportation embedded in information management control system or warehouse management control system with high precision, stable and reliable performance, the low product cost.
Bilingual teaching is the inevitable reform and development trend of higher education, and it is a very important job for us to evaluate the bilingual teaching quality. Currently, we do not have an effective evaluation system for bilingual teaching quality. In this study, the factors which affect bilingual teaching quality are analyzed and the evaluation index system of bilingual teaching quality in universities is established firstly. Then, a knowledge rule mining method for the evaluation of bilingual teaching quality in universities based on an improved genetic algorithm is proposed. In the algorithm, selection operator, dual crossover operator and dual mutation operator are used to generate new knowledge rules. Knowledge rules are evaluated by their accuracy, coverage and reliability. Experimental results show that this knowledge rule mining method is feasible and valid.
Aiming at BP neural network algorithms limitation such as falling into local minimum easily and low convergence speed, an improved BP algorithm with two times adaptive adjust of training parameters (TA-BP algorithm) was proposed. Besides the adaptive adjust of training rate and momentum factor, this algorithm can gain appropriate permitted convergence error by adaptive adjust in the course of training. TA-BP algorithm was applied in fault diagnosis of power transformer. A fault diagnosis model for power transformer was founded based on neural network. The illustrational results show that this algorithm is better than traditional BP algorithm in both convergence speed and precision. We can realize a fast and accurate diagnosis for power transformer fault by this algorithm.
In order to solve knapsack problems efficiently, an improved genetic algorithm based on adaptive evolution in dual population (called DPAGA) is proposed. In DPAGA, the new population produced by selecting operation is regarded as main population. The population composed by the individuals washed out by selecting operation is regarded as subordinate population. The individual evolution strategy of main population is different from that of subordinate population. The crossover operators and mutation operators are all adjusted non-linearly and adaptively. DPAGA is used to solve knapsack problems. The experimental results show that its convergence speed and solution quality are all better then that of simple genetic algorithm. It is also suited to solve other optimization problems.
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