China's carbon emissions trading and stock returns

Wen, Fenghua; Wu, Nan; Gong, Xu

doi:10.1016/j.eneco.2019.104627

Cited by 166 publications

(54 citation statements)

References 57 publications

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“…BP network is used as the evaluation method of performance evaluation index system of landscape simulation system to improve the efficiency of performance evaluation [17]. In general, BP network is constructed by input layer, hidden layer, and output layer to connect all layers in a fully interconnected way, and the cells in the same layer are not connected to each other [18]. e learning process of BP network is formed by forward propagation and backward propagation.…”

Section: Evaluation Method Backpropagation (Bp) Network Hasmentioning

confidence: 99%

Interactive Application of Virtual Reality and Intelligent Big Data in Landscape Design

Zhan

2021

Security and Communication Networks

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In order to improve the accuracy and efficiency of performance evaluation, the interactive application of virtual reality and intelligent big data in landscape design is proposed. Clara algorithm is used to mine the performance evaluation index data of landscape simulation design. The performance evaluation index system of landscape simulation system is established based on the data mined. BP network is used to build a comprehensive evaluation model. The expert scoring method is the evaluation index system scoring, which is used as the input of BP network, and the expected output is a neuron. The value of the neuron represents the comprehensive performance evaluation value of the landscape simulation system. The experimental results show that the evaluation results of the research method are consistent with the expert evaluation results, with high accuracy; with the increasing number of systems, the evaluation efficiency of the research method is faster.

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Section: Evaluation Method Backpropagation (Bp) Network Hasmentioning

confidence: 99%

Interactive Application of Virtual Reality and Intelligent Big Data in Landscape Design

Zhan

2021

Security and Communication Networks

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“…ere are many studies that have shown that combination forecasting can effectively promote the prediction accuracy of stock returns. e combination approach includes two modes: one is to combine the prediction variables (see, e.g., Kelly and Pruitt [41]; Bahrami et al [42]; Pettenuzzo et al [21]), and the other is to combine the popular models (see, e.g., [43][44][45][46][47][48]). Following the literature of Dai and Zhu [25], we employ a mixed model by mixing existing forecasting models to further study stock return forecasts.…”

Section: Mixing Existing Modelmentioning

confidence: 99%

Predicting Stock Return with Economic Constraint: Can Interquartile Range Truncate the Outliers?

Dai

Chang

2021

Mathematical Problems in Engineering

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We find that imposing economic constraint on stock return forecasts based on the Interquartile Range of equity premium can significantly strengthen predictive performance. Specifically, we construct a judgment mechanism that truncates the outliers in forecasts of stock return. We prove that our constraint approach can realize more accurate predictive information relative to the unconstraint approach from the perspective of statistics and economics. In addition, the new constraint approach can effectively defeat CT constraint and CDA strategy. The three mixed models we proposed can further enhance the accuracy of prediction, especially the mixed model combined with our constraint approach. Finally, utilizing our new constraint approach can help investors obtain considerable economic gains. With the application of extension and robustness analysis, our results are robust.

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“…According to the analysis results of the standard deviation of the image block of the aircraft landing gear, the threshold segmentation method is further used to detect the image cracks [19][20][21]. Threshold segmentation is a method of directly segmenting the detected image target area.…”

Section: Implementation Of Intelligent Detection Of Internal Cracks In Aircraft Landing Gear Imagesmentioning

confidence: 99%

Intelligent Detection Method for Internal Cracks in Aircraft Landing Gear Images under Multimedia Processing

Luo

Zhang

2021

Symmetry

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In view of the lack of image enhancement processing in the traditional methods in image preprocessing, which leads to a long detection time for internal cracks in the image and poor visual effects, an intelligent detection method for internal cracks in aircraft landing gear images under multimedia processing is proposed. A spatial index structure is established based on the multimedia database, and the aircraft landing gear images in the structure are enhanced and denoised. Image segmentation is performed according to the preprocessing results, the crack foreground and the road surface background in the image are separated, and the threshold value of each image is calculated. The threshold segmentation result is used to distinguish which pixels are the areas where the cracks may exist and which pixels belong to the image background, and the judgment result realizes crack detection. The experimental results show that the crack detection time of the proposed method is shorter, the visual effect of the detection results is better, and the average of the expert score reaches 93.6 points, which verifies the effectiveness of the proposed method from both the subjective and objective aspects.

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China's carbon emissions trading and stock returns

Cited by 166 publications

References 57 publications

Interactive Application of Virtual Reality and Intelligent Big Data in Landscape Design

Interactive Application of Virtual Reality and Intelligent Big Data in Landscape Design

Predicting Stock Return with Economic Constraint: Can Interquartile Range Truncate the Outliers?

Intelligent Detection Method for Internal Cracks in Aircraft Landing Gear Images under Multimedia Processing

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