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Forecasting solar still performance from conventional weather data variation by machine learning method

Chinese Physics B 2023年第4期32卷 19-25页

作者：高文杰沈乐山孙森山彭桂龙申震王云鹏 AbdAllah Wagih Kandeal 骆周扬 A.E.Kabeel 张坚群鲍华杨诺 State Key Laboratory of Coal Combustion and School of Energy and Power EngineeringHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Baima Lake Laboratory Co. Ltd.Hangzhou 31121China Zhejiang Energy Group R&D Institute Co.Ltd.Hangzhou 311121China Zhejiang Zheneng Yueqing Electric Power Generation Co. Ltd.Yueqing 325609China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong UniversityShanghai 200240China Mechanical Engineering Department Faculty of EngineeringKafrelsheikh UniversityKafrelsheikh 33516Egypt Mechanical Power Engineering Department Faculty of EngineeringTanta UniversityTantaEgypt Faculty of Engineering Delta University for Science and TechnologyGamasaEgypt

Solar stills are considered an effective method to solve the scarcity of drinkable ***,it is still missing a way to forecast its ***,it is proposed that a convenient forecasting model which just needs to input the conventional weather forecasting *** model is established by using machine learning methods of random forest and optimized by Bayesian *** required data to train the model are obtained from daily measurements lasting9 *** validate the accuracy model,the determination coefficients of two types of solar stills are calculated as 0.935and 0.929,respectively,which are much higher than the value of both multiple linear regression(0.767)and the traditional models(0.829 and 0.847).Moreover,by applying the model,we predicted the freshwater production of four cities in *** predicted production is approved to be reliable by a high value of correlation(0.868)between the predicted production and the solar *** the help of the forecasting model,it would greatly promote the global application of solar stills.

关键词： solar still production forecasting forecasting model weather data random forest

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A Non-Destructive Time Series Model for the Estimation of Cherry Coffee Production

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Computers, Materials & Continua 2022年第3期70卷 4725-4743页

作者： Jhonn Pablo Rodríguez David Griol Zoraida Callejas Juan Carlos Corrales Telematics Engineering Group University of CaucaPopayán190002Colombia INRAE University of ToulouseUMR 1248 AGIRF-31326Castanet TolosanFrance Department of Software Engineering University of GranadaGranada18071Spain

Coffee plays a key role in the generation of rural employment in *** than 785,000 workers are directly employed in this activity,which represents the 26%of all jobs in the agricultural *** coffee growers estimate the production of cherry coffee with the main aim of planning the required activities,and resources(number of workers,required infrastructures),anticipating negotiations,estimating,price,and foreseeing losses of coffee production in a specific *** important processes can be affected by several factors that are not easy to predict(e.g.,weather variability,diseases,or plagues.).In this paper,we propose a non-destructive time series model,based on weather and crop management information,that estimate coffee production allowing coffee growers to improve their management of agricultural activities such as flowering calendars,harvesting seasons,definition of irrigation methods,nutrition calendars,and programming the times of concentration of production to define the amount of personnel needed for *** combination of time series and machine learning algorithms based on regression trees(XGBOOST,TR and RF)provides very positive results for the test dataset collected in real conditions for more than a *** best results were obtained by the XGBOOST model(MAE=0.03;RMSE=0.01),and a difference of approximately 0.57%absolute to the main harvest of 2018.

关键词： Cherry coffee production estimation learner approaches time series weather data crop management data

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VARIABILITY OF BUILDING SIMULATION RESULTS DEP ENDING ON SELECTED weather FILES AND CONDITIONING SET POINTS-A CASE STUDY FOR A RESIDENTIAL BUILDING IN VICTORIA,AUSTRALIA

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Journal of Green Building 2016年第4期11卷 91-108页

作者： Astrid Roetzel School of Architecture and Built Environment Deakin UniversityGeelong Waterfront Campus

Building simulation is a powerful way to evaluate the performance of a *** quality of simulation results however strongly depends on the accuracy of simulation input *** for weather data files and occupant behaviour it is difficult to obtain accurate *** paper evaluates the variability of building simulation results with regards to different weather data sets as well as different heating and cooling set points for a residential building in Victoria,*** comfort accord-ing to ASHRAE Standard 55,final energy consumption and peak cooling and heating loads are *** have been performed with Energy-Plus,and weather data for a multi-year approach have been generated with the software *** results show that different weather files for the same location as well as different conditioning set points can influence the results by approximately a factor of 2.

关键词： weather data occupant behaviour heating and cooling set points residential building building simulation energy performance peak loads adaptive thermal comfort

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The First Natural Ventilation Assessment in Building Design in Djibouti

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Journal of Life Sciences 2016年第6期10卷 298-306页

作者： Abdou Idris Omar Abdoulkader Ibrahim Idriss Omar Assowe Dabar Abdourazack Ahmed Kayad Mohamed Said Darar Research Center at the University of Djibouti (CR UD/GRE) Faculty of Engineers Street Djanaleh B.P. 1904 Djibouti Institute for Earth Sciences Centre d'Etudes et de Recherche de Djibouti (CERD) Airportstreet B.P. 486 Djibouti

With a sustained period of economic growth, rapidly growing populations and with more diversified economies Africa need sustainable development; hence the greater need for massive investments in energy. Sub-Saharan countries such as Djibouti have the potential and ability to harness their natural ventilation as a passive cooling system for designing new houses. The rapid expansion of the Djibouti city is affecting negatively the environment and the safety and comfort of its inhabitants. Proper atmospheric urban planning and management are key to making cities environmentally friendly and sustainable. Based on energy consumption, climate conditions in Djibouti and numerical analysis using Computational Fluid Dynamics （CFD）, it is apparent that the natural ventilation creates a thermally comfortable indoor environment in buildings during the cool season of the year. Measured wind data from two measurement systems are presented and discussed. Statistical analyses, wind rose, Weibull distribution were carried out to understand the natural ventilation characteristic, which is used for evolving the basic criteria for economic viability of building in the semi-arid climate of Djibouti. The study found that it is possible to benefit from natural ventilation in buildings during the cool season of the year.

关键词： Computational Fluid Dynamics airflow simulation natural ventilation bioclimatic design weather data energy efficiency.

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基于气象数据的关联规则挖掘

基于气象数据的关联规则挖掘

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第十七届全国数据库学术会议

作者：张宇鹏王丽珍周丽华云南大学计算机科学系

1引言根据气象专家提供的信息,在气象数据中虽然蕴藏有大量气象规律,但难以发现的原因主要有两个:一是数据量巨大,难以做全面细致

关键词： Association rule data variation data mining weather data

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