Functional-type Single-input-rule-modules Connected Neural Fuzzy System for Wind Speed Prediction

Wind is one kind of clean and free renewable energy sources. Wind speed plays a pivotal role in the wind power output. However, due to the random and unstable nature of the wind, accurate prediction of wind speed is a particularly challenging task. This paper presents a novel neural fuzzy method for the hourly wind speed prediction. Firstly, a neural structure is proposed for the functional-type single-input-rule-modules(FSIRMs) connected fuzzy inference system(FIS) to combine the merits of both the FSIRMs connected FIS and the neural network. Then, in order to achieve both the smallest training errors and the smallest parameters, a least square method based parameter learning algorithm is presented for the proposed FSIRMs connected neural fuzzy system(FSIRMNFS). Further,the proposed FSIRMNFS and its parameter learning algorithm are applied to the hourly wind speed prediction. Experiments and comparisons are also made to show the effectiveness and advantages of the proposed approach. Experimental results verified that our study has presented an effective approach for the hourly wind speed prediction. The proposed approach can also be used for the prediction of wind direction, wind power and some other prediction applications in the research field of renewable energy.

Tracking controller design for air handling units with uncertainties

As an important component of the heating,ventilating and air conditioning(HVAC)systems,air handling units(AHUs)are responsible for regulating indoor temperature and humidity.In this paper,a multivariable nonlinear dynamic model of the AHUs with unknown strength of the humidity source is considered,and an improved backstepping controller is proposed to realize the tracking objective of the indoor temperature,relative humidity and carbon dioxide concentration.Firstly,the original system is represented in simplified state space form,and then the state transformation is introduced with a gain to overcome the difficulty caused by the unknown strength of the humidity source.Then,the improved backstepping controller is designed in a step-by-step way.Moreover,the stability of the closed-loop system is analyzed in detail.Finally,we consider the case that the AHUs work in summer of Jinan,China,as an example.The simulation results show the effectiveness of the controller.Meanwhile,the performance of the improved backstepping controller are compared with that of the decoupled sliding mode and PID controllers.

Estimation for ammonia emissions at county level in China from 2013 to 2018

Ammonia (NH_(3)) can interact with other trace chemicals in the atmosphere,significantly impacting atmospheric chemistry and global climate change.China is a largely agricultural country with high consumption of nitrogen fertilizer and large livestock herds,resulting in high NH_(3) emissions.In this study,a comprehensive county-level inventory of Chinese NH_(3) emissions from 2013 to 2018 was compiled.Based on previous research,an estimate of NH_(3) emissions from household coal combustion was added to the inventory.The estimation of emissions from open biomass burning was improved by using a method based on fire radiative energy (FRE).The total NH_(3) emissions in China increased from 2013 (9.64 Tg) to 2015 (9.75 Tg),and then decreased to 9.12 Tg in 2018.Emissions from fossil fuels reached a peak value in 2018,accounting for 8.4%of total emissions,while fertilizer application and livestock waste were responsible for fewer emissions than in previous years,accounting for 27.7%and 49.9%of the total from non-fossil fuel sources,respectively.The highest emission rates were in central and southwestern China.Seasonally,NH_(3) emissions peaked in spring and summer.The inventory had a 1-km spatial resolution and a monthly temporal resolution,which confirmed its suitability for global and regional air quality simulations.

Epidemiology of community pre-hypertensive patients and related risk factors in Chengdu city

Objective:This study aims to explore the epidemiologic characteristics of pre-hypertension,its related risk factors of cardiovascular diseases and its relativity with metabolic disorders among community residents of Chengdu city.Methods:Cluster random sampling was performed in three districts and counties of Chengdu.A total of 3524 residents(resident for≥1 year,≥18 years of age)were enrolled in the investigation.All the participants were interviewed in the questionnaire survey.Physical examination,blood pressure measurements,and blood sampling were also performed.Results:The overall prevalence of pre-hypertension was 34.07%.The prevalence of prehyper-tension was higher in males than in females(41.16%vs.23.89%,P<0.05).The prevalence of pre-hypertension among patients with systolic/diastolic blood pressures of 120-129 mmHg/80-84 mmHg and 130-139 mmHg/85-89 mmHg were 34.90%and 17.16%,respectively.The prevalence of pre-hypertension increased with age,reaching a peak at 30-39 years(39.93%),and then declined.Multi-ple risk factors for cardiovascular disease were more common in patients with hypertension and pre-hypertension than in the population with normal blood pressure.Pre-hypertension was associated with increased fasting blood glucose and increased relative risks of hypertriglyceridemia,hyperuricemia,overweight,obesity,and abdominal obesity,compared with patients who had normal blood pressure.Conclusion:The prevalence of pre-hypertension in residents of Chengdu was high.Multiple metabolic disorders were already present in the population,and multiple cardiovascular disease risk factors were more common than in the population with normal blood pressure.Early screening for cardiovascular risk factors should be performed in patients with pre-hypertension.In addition,comprehensive measures,such as lifestyle improvement and medications,should be implemented.