Pedestrian Reidentification Based on Feature Fusion and Metric Learning

The pedestrian recognition in public environment is influenced by the pedestrian environment and the dynamic characteristic boundary factors, so it is easy to produce the tracking error. In order to improve the ability of pedestrian re-identification in public environment, we need to carry out feature fusion and metric learning, and propose pedestrian re-identification based on feature fusion and metric learning. The geometric grid area model of pedestrian recognition in public environment is constructed, the method of fuzzy dynamic feature segmentation is used to reconstruct the dynamic boundary feature point of pedestrian recognition in public environment, the method of bottom-up modeling is used to design the dynamic area grid model of pedestrian recognition in public environment, the design of dynamic area grid model is three-dimensional grid area, the grayscale pixel set of pedestrian recognition dynamic constraint under public environment is extracted, the boundary feature fusion is carried out according to the distribution intensity of grayscale, the image fusion and enhancement information processing of pedestrian recognition under public environment, and the method of 3D dynamic constraint is used to realize the local motion planning of pedestrian recognition under public environment, and the recognition feature fusion and learning of pedestrian recognition under public environment is realized according to the result of contour segmentation. The simulation results show that the method is used for pedestrian recognition again in public environment, and the fuzzy judgment ability of pedestrian dynamic edge features is strong, which makes the error controlled below 10 mm, and the fluctuation of pedestrian recognition again is more stable, the recognition accuracy is higher and the robustness is better.

Large-scale traffic flow simulation based on intelligent PSO

With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time.

Economic Dispatch Methods for Smart Grid Based on Improved SPEA2 and Improved NSGA2

The severity of the ongoing environmental crisis has prompted the development of renewable energy generation and smart grids integration. The access of enewable energy makes the economic dispatching of smart grid complicated. Therefore, the economic dispatching model for smart grid is very necessary. This paper presents an economic dispatching model of smart power grid, which considers both economy and pollution emission. The smart grid model used for the simulation is construced of wind energy, solar energy, fuel cell, and thermal power, and the use of fuel cell enables the smart grid to achieve multi-energy complementar. To overcome the defect of the traditional centralized communication methods, which are prone to communication jams, this paper adopts a multi-agent inform ation exchange method to improve the stability and efficiency. In terms of the solution method for this model, this paper proposes Improved Strength Pareto Evolutionary Algorithm 2(ISPEA2) and Improved Non-dominated Sorting Genetic Algorithm 2(INSGA2) that solves the economic dispatch problem of a smart grid. The strength Pareto evolutionary algorithm 2(SPEA2),non-dominated sorting genetic algorithm 2(NSGA2) and the improved algorithms are simultaneously applied to the proposed smart grid model for economic dispatching simulation. The simulation results show that ISPEA2 and INSGA2 are effective. ISPEA2 and INSGA2 have shown improvements over SPEA2 and NSGA2 in accuracy or running times.

Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert)

Black carbon (BC) is a primary and inert pollutant often used as a traffic tracer. Even though its concentrations are generally low at the regional scale, BC presents very high concentrations in streets (at the local scale), potentially with important effects on human health and the environment. Modeling studies of BC concentrations usually underestimate BC concentrations due to uncertainties in both emissions and modeling. Both exhaust and non-exhaust traffic emissions present uncertainties, but the uncertainties with respect to non-exhaust emissions, such as tire, brake, and road wear as well as particle resuspension, are particularly high. In terms of modeling, street models do not always consider the two-way interactions between the local and regional scales. Using a two-way modeling approach, a street with high BC concentrations may influence urban background concentrations above the street, which can subsequently enhance the BC concentrations in the same street. This study uses the multiscale Street-in-Grid model (SinG) to simulate BC concentrations in a suburban street network in Paris, taking the two-way coupling between local and regional scales into account. The BC concentrations in streets proved to have an important influence on urban background concentrations. The two-way dynamic coupling leads to an increase in BC concentrations in large streets with high traffic emissions (with a maximal increase of about 48 %) as well as a decrease in narrow streets with low traffic emissions and low BC concentrations (with a maximal decrease of about 50 %). A new approach to estimate particle resuspension in streets is implemented, strictly respecting the mass balance on the street surface. The resuspension rate is calculated from the available deposited mass on the street surface, which is estimated based on particle deposition and wash-off parameterizations adapted to street-canyon geometries. The simulations show that particle resuspension presents a low contribution to BC concentrations, as the deposited mass is not significant enough to justify high resuspension rates. Non-exhaust emissions, such as brake, tire, and road wear, may largely contribute to BC emissions, with a contribution that is equivalent to exhaust emissions. Here, a sensitivity analysis of BC concentrations is performed by comparing simulations with different emission factors of tire, brake, and road wear. The different emission factors considered are estimated based on the literature. We found a satisfying model–measurement comparison using high tire wear emission factors, which may indicate that the tire emission factors usually used in Europe are probably underestimated. These results have important policy implications: public policies replacing internal combustion engines with electric vehicles may not eliminate BC air pollution but only reduce it by half.

Travel Dynamics Analysis and Intelligent Path Rectification Planning of a Roadheader on a Roadway

The tunneling work belongs to the group operation of semi-closed space, and the work is difficult with a high risk coefficient. It is an urgent requirement of coal mining to achieve unmanned and intelligent tunneling work. The path rectification planning of roadheaders is a necessary step before roadway cutting. In the traditional dynamic modeling analysis of roadhead tracks, problems such as compaction resistance, bulldozing resistance, steering resistance, tunnel dip angle, ditching, and obstacle-crossing capacity are not considered. In order to approximate the kinematic and dynamic parameters of a roadheader’s deviation correction under actual working conditions, this paper establishes kinematic and dynamic models of a roadheader’s path rectification at low speeds and under complex working conditions, and calculates the obstacle-crossing ability of roadheaders in the course of path rectification by modes based on roadway conditions, crawler resistance, and driving performance of the roadheader. Field experiments were carried out to verify the effectiveness of the dynamic model. The dynamic roadheader model was used in combination with actual working conditions of roadways in order to establish a roadway grid model. The grid model was simplified using rectifying influence degree and distance cost. The roadheader dynamic model and grid model were then used to propose a path rectification planning and tracking algorithm based on particle swarm optimization of the actual roadway conditions and roadheader driving performance. Finally, the effectiveness and superiority of the algorithm were verified using MATLAB simulation. The algorithm can provide strong technical guarantee for the intelligence of roadheader and unmanned mining. The results presented here can provide theoretical and technical support for the structural optimization and intelligent travel control of roadheaders.

Positioning Koperasi Melalui Pendekatan ICA Grid Model

In order to know whether a cooperative organization is really a cooperative in a true sense, it is necessary to first look at its identity. The identity of a cooperative is a basic characteristic inherent in a cooperative since its birth. It undergoes a very long and crystalline process of growth and maturity, thus placing the cooperative as a business entity that has a positioning for its members. Cooperatives operate in a space that is limited by their identity and by the rules that apply to free market players such as corporations. Cooperatives also play in a competitive market economy and also in an environment where market conditions sometimes do not apply. Therefore for cooperatives it is important to know where their position is at certain times in an effort to maintain and secure their identity, with the aim of maintaining their existence as a cooperative.