This study explores the loss or degradation of the ecosystem and its service function in the Liaohe estuary coastal zone due to the deterioration of water quality. A prediction system based on support vector machine (SVM)-particle swarm optimization (PSO) (SVM-PSO) algorithm is proposed under the background of deep learning. SVM-PSO algorithm is employed to analyze the pollution status of the Liaohe estuary, so is the difference in water pollution of different sea consuming types. Based on the analysis results for causes of pollution, the control countermeasures of water pollution in Liaohe estuary are put forward. The results suggest that the water pollution index prediction model based on SVM-PSO algorithm shows the maximum error of 2.41%, the average error of 1.24% in predicting the samples, the root mean square error (RMSE) of 5.36 × 10 −4 , and the square of correlation coefficient of 0.91. Therefore, the prediction system in this study is feasible. At present, the water pollution status of Liaohe estuary is of moderate and severe levels of eutrophication, and the water pollution status basically remains at the level of mild pollution. The general trend is from phosphorus moderate restricted eutrophication to phosphorus restricted potential eutrophication. To sum up, the SVM-PSO algorithm shows good sewage prediction ability, which can be applied and promoted in water pollution control and has reliable reference significance.
In a power plant, the bellows of the lower part of the expansion joint for pumping and heating of the NO.8 turbo-generator unit breaked, and the internal guide plate was teared along the welding seam. Through observation of macroscopic morphology, hardness analysis, metallographic examination, energy spectrum analysis and other means, the corrugated pipe material itself unqualified performance, stress corrosion cracking, corrosion and other reasons were eliminated. According to the micro-characteristics of fatigue fracture and the service environment of the bellows, it is concluded that the main reason of break is the fatigue cracking of the bellows under the impact of the air flow and vibration.
The air-conditioning load is an important part of the power system’s peak load, significantly impacting the power grid’s safe and stable operation. Therefore, it is necessary to evaluate the air-conditioning load’s adjustment potential, providing a reference for the power grid to formulate a reasonable dispatch plan, participate in the demand-side response, and alleviate the insufficient power-side regulation capacity caused by the large-scale access of intermittent renewable energy. This paper mainly obtains the air-conditioning load curve under different conditions through the characteristics of residents’ electricity usage behavior and analyzes the adjustable air-conditioning load capacity based on load plasticity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.