Research on Dynamic Scheduling of Unbalanced Supply and Demand of the SROC Based on the Customers Priority Principle

The problem of imbalance between supply and demand in car-sharing scheduling has greatly restricted the development of car-sharing. This paper first analyzes the three supply and demand modes of car-sharing scheduling systems. Secondly, for the station-based with reservation one-way car-sharing problem (SROC), this article establishes a dynamic scheduling model under the principle of customer priority. The model introduces balance coefficients to predict the balance mode, and systematically rebalance the fleet networks in each period. In the case of meeting customer needs, the model objective function is to maximize the total profit and minimize the scheduling and loss costs. Then, in view of the diversity and uncertainty of scheduling schemes, a scheme information matrix is constructed. In the iterative process of genetic algorithm, individuals are selected and constructed according to the pheromone matrix, and evolution probability is proposed to control the balance between global search and local search of genetic algorithm. Finally, the data of Haikou City is used for simulation experiment.

Intelligent early warning method based on drone inspection

Commonly used UAV emergency inspection methods are executed by the instructions of the ground command center. The response rate depends on the stability of the communication network and the rapid response ability of the commander. The critical time window is fleeting, which is likely to cause unnecessary loss. Crisis rapid response capability has become the key to measuring system capabilities. In order to improve the system’s rapid response capability, a method of deploying decision-making agents on airborne computers and ground early warning systems is proposed. This early warning method uses key technologies such as multi-network integration, situation assessment, neural network architecture, deep learning, reinforcement learning, and intelligent cognitive reasoning to effectively ensure the effectiveness of crisis warning. The early warning method of the early warning system is as follows: the mission computer uniformly collects the flight control status parameters, the load status parameters and the load real-time data form a composite information flow. The task computer adopts the methods of protocol conversion, data classification, and danger recognition to the compound information flow to identify the crisis information and make a preliminary analysis and judgment of the crisis state. If it is determined that it is necessary to track the target in real time, the initial task assignment and parameter adjustment of the load are carried out, and the continuous tracking of the task target is carried out to realize the rapid response to the crisis on the edge side. At the same time, the composite data are downloaded to the command center. The command center performs the secondary crisis analysis and risk level determination and outputs the crisis plan deduced by the agent to realize the strategy assistance. The accuser refers to the plan strategy and issues instructions to the task computer, and the task computer receives it. Instruction and secondary adjustment and optimization of the load parameters. If there is a flight route adjustment instruction, the adjustment route will be sent to the flight controller, which greatly improves the flexibility and efficiency of handling the crisis in the UAV inspection process. By adopting this set of early warning methods, it can provide users with an updated, faster and more efficient way to realize the early warning requirements in drone inspections, which is a new breakthrough in the field of drone command methods.

Multifactor Uncertain Chemical Reaction Equation

The previous uncertain chemical reaction equation describes the time evolution of single reactions. But in many practical cases, a substance is consumed by several different reaction pathways. For the above considerations, this paper extends the discussion to multiple reactions. Specifically, by taking the decomposition of C2H5OH as an example, parallel reactions with one reactant are analyzed with the multifactor uncertain differential equation. The derived equation is called the multifactor uncertain chemical reaction equation. Following that, the parameters in the multifactor uncertain chemical reaction equation are estimated by the generalized moment estimation. Based on the multifactor uncertain chemical reaction equation, half-life of reaction is investigated. Finally, a numerical example is presented to illustrate the usefulness of the multifactor uncertain chemical reaction equation.

A novel second-order adaptive grid method for singularly perturbed convection–diffusion equations

In this paper, a singularly perturbed convection–diffusion equation is studied. At first, the original problem is transformed into a parameterized singularly perturbed Volterra integro-differential equation by using an integral transform. Then, a second-order finite difference method on an arbitrary mesh is given. The stability and local truncation error estimates of the discrete schemes are analyzed. Based on the mesh equidistribution principle and local truncation error estimation, an adaptive grid algorithm is given. In addition, in order to calculate the parameters of the transformation equation, a nonlinear unconstrained optimization problem is constructed. Numerical experiments are given to illustrate the effectiveness of our presented adaptive grid algorithm.

Difference double sequence of complex uncertain variables defined by Orlicz function

In this paper, we introduce the difference double sequence of complex uncertain variables defined by Orlicz function. We study some of their properties like solidness, symmetricity, and completeness and prove some inclusion results.

On rough convergence of complex uncertain sequences

Complex uncertain variables are measurable functions from an uncertainty space to the set of complex numbers and are used to model complex uncertain quantities. The main purpose of this paper is to introduce rough convergence of complex uncertain sequences and study some convergence concepts namely rough convergence in measure, rough convergence in mean, rough convergence in distribution of complex uncertain sequences. Lastly some relationship between them have been investigated.

Cross Entropy Chance Distribution Model of Uncertain Random Shortest Path Problem

The shortest path problem (SPP) is one of the most typical and basic optimization problems in network theory for decades, and it covers a series of practical application problems, such as urban planning, logistics transportation, engineering and power grid strain analysis, etc. The circumstance where the weight of arcs in a network contains both randomness and uncertainty is considered, and the case of the weights of arcs with uncertain random variables is focused on in this paper. Here, we introduced a new model of the SPP which is based on the new definition of uncertain random variables cross entropy, and the newly established model can be used to find the path with the closest chance distribution to the ideal SP. The efficiency of this model is also evaluated in the final part.

Uncertain Independent Increment Processes are Contour Processes

Uncertain processes are used to model dynamic indeterminate systems associated with human uncertainty, and uncertain independent increment processes are a type of uncertain processes with independent uncertain increments. This paper mainly verifies a basic property about the sample paths of uncertain independent increment processes, which states that uncertain independent increment processes defined on a continuous uncertainty space are contour processes, a type of uncertain processes with a spectrum of sample paths as the skeletons. Based on this property, the extreme values and the time integral of an uncertain independent increment process are investigated, and their inverse uncertainty distributions are obtained.

Uncertain Circuit Equation

Differential equation is a powerful tool for investigating the transient and steady-state solutions of electrical circuit in the time domain. By considering the noise in actual circuit system, this paper first presents an uncertain circuit equation, which is a type of differential equation driven by Liu process. Then the solution of uncertain circuit equation and the inverse uncertainty distribution of solution are derived. Following that, two applications of solution are provided as well. Based on the observations, the method of moments is used to estimate the unknown parameters in uncertain circuit equation. In addition, a paradox for stochastic circuit equation is also given.

A Short-Turning Strategy for the Management of Bus Bunching Considering Variable Spatial-Temporal Running Time

Bus bunching could seriously damage the stability of transit system. This resultant instability always causes a dissatisfying performance of transit system. Traditional bus bunching control methods (e.g., holding control strategy) add slack to schedules or adapt cruising speed. The control methods can alleviate bus bunching in theory, but it is difficult to apply to actual operation, especially in busy traffic. The short-turning strategy only deals with spatial concentration of demand in the existing literatures. We find that the short-turning strategy is also very effective in alleviating bus bunching. In this study, based on the passenger arrival rate of each stop and the spatial-temporal running time, a short-turning model with bunching penalty is developed, and the waiting time of passengers and the operation cost are also considered. Based on data from Beijing Transportation Information Center, we take the Yuntong 111 bus line of Beijing as an example. Compared with the currently used timetable, it is found that a 46.78% reduction in bus bunching is achieved by using the optimal timetable, and there is no increase in operating costs.