This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time...This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time intervals through training the WNN with even time-interval samples. The method builds successive new model with the width of sliding window remaining invariable so as to obtain a dynamic prediction method for gas emission quantity. Furthermore, the method performs prediction by a self-developed WNN toolbox. Experiments indicate that such a model can overcome the deficiencies of the traditional static prediction model and can fully make use of the feature extraction capability of wavelet base function to reflect the geological feature of gas emission quantity dynamically. The method is characterized by simplicity, flexibility, small data scale, fast convergence rate and high prediction precision. In addition, the method is also characterized by certainty and repeatability of the predicted results. The effectiveness of this method is confirmed by simulation results. Therefore, this method will exert practical significance on promoting the application of WNN.展开更多
This article summarizes and analyzes the Children & Youth Forum and youth participation in the process during and leading up to the Third UN World Conference on Disaster Risk Reduction(WCDRR) in2015. An organizing...This article summarizes and analyzes the Children & Youth Forum and youth participation in the process during and leading up to the Third UN World Conference on Disaster Risk Reduction(WCDRR) in2015. An organizing committee consisting of international students and young professionals brought together around200 young professionals and students from around the globe to exchange ideas and knowledge on reducing disaster risk, building resilient communities, and advocating for the inclusion of youth priorities within the Sendai Framework for Disaster Risk Reduction 2015–2030(SFDRR). The knowledge exchange during the Forum was structured around a Toolbox for Resilience that connected to the SFDRR section on Priorities for Action. This article presents the outcomes of these young people’s participation in the disaster risk reduction capacity building eventsand policy-making, as well as the follow-up actions envisioned by the young participants of the Forum. The voices of the younger generation were heard in the SFDRR and young people are ready to expand their actions for the framework’s effective implementation. Young people call on technical experts, donors, NGOs, agencies, governments, and academia to partner with them on this journey to create a more resilient tomorrow together.展开更多
文摘This paper presents a method for dynamically predicting gas emission quantity based on the wavelet neural network （WNN） toolbox. Such a method is able to predict the gas emission quantity in adjacent subsequent time intervals through training the WNN with even time-interval samples. The method builds successive new model with the width of sliding window remaining invariable so as to obtain a dynamic prediction method for gas emission quantity. Furthermore, the method performs prediction by a self-developed WNN toolbox. Experiments indicate that such a model can overcome the deficiencies of the traditional static prediction model and can fully make use of the feature extraction capability of wavelet base function to reflect the geological feature of gas emission quantity dynamically. The method is characterized by simplicity, flexibility, small data scale, fast convergence rate and high prediction precision. In addition, the method is also characterized by certainty and repeatability of the predicted results. The effectiveness of this method is confirmed by simulation results. Therefore, this method will exert practical significance on promoting the application of WNN.
文摘This article summarizes and analyzes the Children & Youth Forum and youth participation in the process during and leading up to the Third UN World Conference on Disaster Risk Reduction(WCDRR) in2015. An organizing committee consisting of international students and young professionals brought together around200 young professionals and students from around the globe to exchange ideas and knowledge on reducing disaster risk, building resilient communities, and advocating for the inclusion of youth priorities within the Sendai Framework for Disaster Risk Reduction 2015–2030(SFDRR). The knowledge exchange during the Forum was structured around a Toolbox for Resilience that connected to the SFDRR section on Priorities for Action. This article presents the outcomes of these young people’s participation in the disaster risk reduction capacity building eventsand policy-making, as well as the follow-up actions envisioned by the young participants of the Forum. The voices of the younger generation were heard in the SFDRR and young people are ready to expand their actions for the framework’s effective implementation. Young people call on technical experts, donors, NGOs, agencies, governments, and academia to partner with them on this journey to create a more resilient tomorrow together.
