This paper describes our system in the Chinese Grammatical Error Diagnosis (CGED) task for learning Chinese as a Foreign Language (CFL). Our work adopts a hybrid model by integrating rulebased method and n-gram statistical method to detect Chinese grammatical errors, identify the error type and point out the position of error in the input sentences. Tri-gram is applied to disorder mistake. And the rest of mistakes are solved by the conservation rules sets. Empirical evaluation results demonstrate the utility of our CGED system.
This paper compared the expected accuracy of the gray GM (1, 1) model and the combined GMBP model using a data set for major road traffic accidents. A combined GMBP prediction model composed of the very first parameter gray model GM (1, 1) is able to make exact predictions for forecasting dreary type of processes, and BP (back-propagation) neural network for a major traffic accident is proposed to overcome the limitations of a single prediction model for a major traffic accident. The method first obtains predicted data using the gray GM (1, 1) model, then trains the BP neural network using the GM (1, 1) model’s predicted data and the original data as input and output data, respectively, and finally the trained BP neural network can be considered a combined GMBP prediction model. The predicted data of the digit of major traffic accidents, the digit of fatalities, and the digit of damages from 2008 to 2020 were obtained using the combined GMBP prediction model, and it is compared with the expected data of the single gray GM (1, 1) model. The grades showed that the exactitude of the combined GMBP prediction model was significantly higher than that of the single gray GM (1, 1) model. Finally, from 2021 to 2033, the combined GMBP prediction model is used to forecast the number of significant road traffic incidents, mortalities, and damages. The prediction results show that the number of accidents, faculties, and injuries is on the decline in the future years.
With the rapid development of cities, traffic congestion appears more or less in large and small cities. With the continuous increase of motor vehicles, problems such as traffic congestion, energy shortage and environmental pollution have also appeared one after another. Urban traffic problems are getting worse, and urban congestion needs to be solved urgently. This article focuses on the optimization of urban land layout, expansion of urban transportation infrastructure construction, strict control of the total number of vehicles, priority development of public transportation, and vigorous development of intelligent transportation systems. Countermeasures and solutions are proposed in this paper to alleviate traffic congestion and to make effective suggestions.
Vehicle parking is not only an important problem in urban traffic, but also an important factor affecting the relationship between cities and within cities. In this paper, by investigating the parking conditions of Jiaozuo Wanda Plaza in 2018, important parameters such as average parking time on weekdays and holidays, berth turnover rate, parking utilization rate and centralized parking index were obtained. Based on the obtained parameters, multi-angle optimization analysis was conducted on the parking lot. In order to reduce the congestion of the entrance and exit of parking lots and improve parking efficiency, this paper adopts the method of increasing the entrance and exit of parking lots and optimizing the route. It has great reference value in practical application.
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