Effect Evaluation and Intelligent Prediction of Power Substation Project Considering New Energy

The evaluation of the implementation effect of the power substation project can find out the problems of the project more comprehensively,which has important practical significance for the further development of the power substation project.To ensure accuracy and real-time evaluation,this paper proposes a novel hybrid intelligent evaluation and prediction model based on improved TOPSIS and Long Short-Term Memory(LSTM)optimized by a Sperm Whale Algorithm(SWA).Firstly,under the background of considering the development of new energy,the influencing factors of power substation project implementation effect are analyzed from three aspects of technology,economy and society.Moreover,an evaluation model based on improved TOPSIS is constructed.Then,an intelligent prediction model based on SWA optimized LSTM is designed.Finally,the scientificity and accuracy of the proposed model are verified by empirical analysis,and the important factors affecting the implementation effect of power substation projects are pointed out.

An scientific evaluation of annual earthquake prediction ability

The scientific idea of earthquake prediction in China is introduced in this paper. The various problems on evaluation of earthquake prediction ability are analyzed. The practical effect of prediction on annual seismic risk areas in 1990~2000 in China is discussed based on R-value evaluation method, and the ability of present earthquake prediction in China is reviewed.

Application of apparent stress in earthquake prediction

On the basis of the assumption that ω^2 model accords with source displacement spectra of moderate-small shocks, we calculate the apparent stress values of 1 020 moderate-small shocks recorded by the Digital Seismic Network of Yunnan Province by using the low-frequency fiat level and corner frequencies. The results show that the apparent stress is of good significance in earthquake prediction. The moderate-small shock with apparent stress larger than 0.9 MPa can be used as a referential index to predict moderate-strong earthquakes in Yunnan area. And its relevant predictability evaluation （R value） has a high confidence level.

RS and GIS-based Statistical Analysis of Secondary Geological Disasters after the 2008 Wenchuan Earthquake

Using RS and GIS means, this article analyzes the general geological characteristics and the structural belt distribution features in Wenchuan County, Sichuan province, P.R. China as well as the characteristics of the large-scale landslides, mud-rock flows, earthquake lakes, etc., after the earthquake on May 12, 2008. Based on the above work, comprehensive indoor and outdoor research is launched on disaster distribution characteristics and their relationship with earthquakes, terrains, strata, lithology, and structures. Weights of evidence method is utilized to quantitatively analyze and evaluate the spatial distribution of secondary geological disasters after the earthquake occurred. 3 remedying grades for secondary geological disasters are derived from the results of the weights of Evidence, followed by suggestions given to remedy earthquake secondary disasters.

Urban Ecosystem Prediction and Comprehensive Evaluation Ideology

In the light of the study of domestic and foreign ur-ban ecosystem,this article puts forward a set of ideological systemsfor the forecast,evaluation and tactic,and conducts initial primaryexploration of its forecast and evaluation methods.

Accelerating the detection of unfeasible hypothetical zeolites via symmetric local interatomic distance criteria

In silico prediction of potential synthetic targets is the prerequisite for function-led discovery of new zeolites. Millions of hypothetical zeolitic structures have been predicted via various computational methods, but most of them are experimentally inaccessible under conventional synthetic conditions.Screening out unfeasible structures is crucial for the selection of synthetic targets with desired functions.The local interatomic distance（LID） criteria are a set of structure rules strictly obeyed by all existing zeolite framework types. Using these criteria, many unfeasible hypothetical structures have been detected. However, to calculate their LIDs, all hypothetical structures need to be fully optimized without symmetry constraints. When evaluating a large number of hypothetical structures, such calculations may become too computationally expensive due to the forbiddingly high degree of freedom. Here, we propose calculating LIDs among structures optimized with symmetry constraints and using them as new structure evaluation criteria, i.e., the LIDsymcriteria, to screen out unfeasible hypothetical structures. We find that the LIDsymcriteria can detect unfeasible structures as many as the original non-symmetric LID criteria do, yet require at least one order of magnitude less computation at the initial geometry optimization stage.