Optimized vehicle scheduling and filling model based on effective space and integrated solving algorithm

We established an integrated and optimized model of vehicle scheduling problem and vehicle filling problem for solving an extremely complex delivery mode-multi-type vehicles, non-full loads, pickup and delivery in logistics and delivery system. The integrated and optimized model is based on our previous research result-effective space method. An integrated algorithm suitable for the integrated and optimized model was proposed and corresponding computer programs were designed to solve practical problems. The results indicates the programs can work out optimized delivery routes and concrete loading projects. The model and algorithm have many virtues and are valuable in practice.

An Easy Algorithm for Solving Radiative Transfer Equation in Clear Atmosphere

An accurate and rapid method for solving radiative transfer equation is presented in this paper. According to the fact that the multiple scattering component of radiance is less sensitive to the error of phase function than the single scattering component is,we calculate the multiple scattering component by using delta-Eddington approximation and the single scattering component by solving radiative transfer equation. On the ground, when multiple sattering component is small, for example, when the total optical depth T is small, the accurate radiance can be obtained with this method. For the need of the space remote sensing, the upward radiance at the top of the atmosphere is mainly studied, and an approximate expression is presented to correct the multiple scattering component. Compared with the more precise Gauss-Seidel method.the results from this method show an accuracy of better than 10% when zenith angle 0 < 50 掳 and T < 1. The computational speed of this method is, however, much faster than that of Gauss-Seidel method.

Determination of a Numerical Analysis Algorithm for the Regulation of Blood Sugar in Diabetics

Acceptable glycemic control when examining the effects of meals was achieved when combining basal insulin therapy and high concentration insulin injection before a meal, when using a PID controller (Proportionality, Integrity and Derivative actions) alone, when using a PID controller with basal insulin therapy and when combining the three methods of insulin delivery. Naturally, a type 1 diabetic must inject himself with insulin in well-measured doses. Thus, the management and control of diabetes become a complex task when one must be considered the disturbance due to nutrition and sports activity. This concern has been at the center of much research through different approaches through mathematical methods and Artificial Intelligence methods. This article simulates a physiological model of glycemic control in type 1 diabetics by a PID regulatory mechanism, in the context of disturbances caused by the patient’s meals and athletic activity.

Some mistakes in the algorithm for solving underflow problem in Baum-Welch algorithm and their corrections

Baum-Welch algorithm most likely results in underflow in practice. In some literatures, such as 'Scaling' algorithm was introduced to solve the problem. In applications, however, some mistakes were found in the equations presented in these literatures. The practical calculations show that the original algorithm often results in poor or even none convergence and rather higher error rate in speech recognition. The mistakes in these literatures and brings forward the correct equations are analysed. The speech recognition system using the revised algorithm can converge well and has lower error rate.

A COLUMN RECURRENCE ALGORITHM FOR SOLVING LINEAR LEAST SQUARES PROBLEM

A new column recurrence algorithm based on the classical Greville method and modified Huang update is proposed for computing generalized inverse matrix and least squares solution. The numerical results have shown the high efficiency and stability of the algorithm.

Data-driven evacuation and rescue traffic optimization with rescue contraflow control

In response to local sudden disasters,e.g.,high-rise office or residential building fire disasters,road occupation can cause conflicts,and traffic directions may be opposite between evacuation vehicles and rescue vehicles;moreover,lane contraflow can be adopted to meet these surge traffic demands.However,lane contraflow that provides more roads for rescue vehicles reduces the traffic supply in the evacuation direction.It is unclear how to control the number of contraflow roads used by rescue vehicles to coordinate evacuation and rescue traffic operations.Here,we adjust the critical rescue traffic volume of reversing the normal road traffic direction to control rescue contraflow.Additionally,we propose a multiobjective mixed integer linear programming formulation for evacuation and rescue traffic optimization.Additionally,considering that the upper limit of the critical rescue traffic volume is unknown and that the proposed formulation includes multiple objectives and multi-priority vehicle classes,a three-stage solving algorithm is developed.Next,a large-scale evacuation and rescue traffic optimization result dataset is obtained for the Nguyen–Dupuis road network,and the impact of different rescue contraflow control plans on evacuation and rescue traffic is studied based on data-driven sta-tistical analysis.The results show that by adjusting the optimal rescue traffic route,the critical rescue traffic volume for reversing the normal road traffic direction can reduce the interference of rescue traffic to evacuation traffic operation performance without reducing rescue traffic operation performance,and can be used to coor-dinate evacuation and rescue traffic operation under rescue contraflow.