Abstract
The mathematical model of biochemical analysis system was established based on neural network-greedy algorithm. The optimal task scheduling sequence was solved by neural network algorithm. At the same time, the local optimization was obtained by combining greedy algorithm. In this way, the task scheduling problem in biochemical analyzer was transformed into a mathematical problem, and the mathematical model of scheduling algorithm was established. On the platform of MATLAB, eight groups of simulation tests were carried out on the same task scheduling problem using the neural network-greedy scheduling algorithm and the traditional fixedperiod scheduling algorithm. The task-time Gantt charts of the two algorithms were compared under different scheduling orders. The results showed that the average speed of the neural network-greedy algorithm was improved by 31% compared with that of the fixed-period scheduling algorithm. The mathematical model of biochemical analysis system on scheduling problem established by neural network-greedy scheduling algorithm has high efficiency compared with the traditional fixed-period scheduling algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
