In this paper, we propose a novel method to monitor and analyze the renewable energy using intelligent algorithm. The main innovation of this paper lies in that we introduce time series algorithm to monitor and analyz...
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ISBN:
(纸本)9781467393935
In this paper, we propose a novel method to monitor and analyze the renewable energy using intelligent algorithm. The main innovation of this paper lies in that we introduce time series algorithm to monitor and analyze of utilization of renewable energy. In particular, three types of building integrated renewable energy sources are utilized, including 1) Solar water heater, 2) Solar photovoltaic, and 3) Ground source heat pump. Next, the renewable energy monitor and analysis system is implemented using the hidden Markov model, which can effectively describe the intrinsic connection between observed data. Finally, we utilize 1) utilization efficiency, 2) solar radiation quantity and 3) COP value as the performance evaluation metric to test the performance of the proposed method. Experimental results show that the monitor and analysis results for renewable energy system by our method are very close to real values.
As global warming getting more severe in recent decades, the seawater temperature has also increased dramatically, which leads Atlantic fish heading north, so are two important economic fish spcies in Scotland, Scotti...
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As global warming getting more severe in recent decades, the seawater temperature has also increased dramatically, which leads Atlantic fish heading north, so are two important economic fish spcies in Scotland, Scottish herring and mackerel. This paper discusses the impact of temperature change on the two species, and offer improvement methods for the small Scotland-based fishing companies. According the history temperature data in Scotland and the surrounding waters, we use a time series algorithm to predict the temperature range over next 50 years. Then establish a cost equation with parameters based on the relative distance and temperature. We obtain minimum cost from the predicted temperature and the relative distance from shoals. The result shows that in the next 50 years, a portion of the Scottish herring will move first northeast and then north, and the mackerel will move near the coast of Norway. The speed range of fish is obtained from previous model. Furthermore, maximum range of fishing time is obtained under different fish migration speed and fishing vessel speed. The best, worst and most likely case for fishing companies are defined and found. Which are they can fish before 2033 at lowest fish migration speed, they can not fish at the highest speed after 2051, and can not sell fresh fish anymore at 2040 respectively.
The thesis uses data in the database of campus card platform as the analysis object, combined with statistical methods and data mining technology to analyze the students' consumption and the situation of the cante...
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ISBN:
(纸本)9783037859391
The thesis uses data in the database of campus card platform as the analysis object, combined with statistical methods and data mining technology to analyze the students' consumption and the situation of the canteens. We use the Microsoft .NET and SQL Server 2008 business intelligence development tools to mine and analyze these data;know canteen's consumption and learn about the business status and the popular shops of the canteen by using the K-means algorithm;analyze and predict students' behavior and the situation of the canteen by using time series algorithm. It is convenient to manage the college students, and provide data support for university policy makers and shoppers to make plans.
In this paper, using the NFLIS data and the U.S. Census socio-economic data and a variety of scientific ideas and algorithms to construct a time-society model(TS model). The dissemination patterns and characteristics ...
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In this paper, using the NFLIS data and the U.S. Census socio-economic data and a variety of scientific ideas and algorithms to construct a time-society model(TS model). The dissemination patterns and characteristics of opioids and heroin are analyzed, while the future development trend is forecasted. At the same time, potential influencing factors leading to the current situation are excavated and effective strategies are proposed to fight the opioid crisis.
The ongoing Russia-Ukraine war has an impact on air quality in the contested region, but it is difficult to assess it during the war and to distinguish between weather conditions and anthropogenic impacts on air pollu...
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The ongoing Russia-Ukraine war has an impact on air quality in the contested region, but it is difficult to assess it during the war and to distinguish between weather conditions and anthropogenic impacts on air pollution. Aerosol optical depth (AOD) might be a way to indicate the regional air quality remotely. In this study, we analyze satellite-based MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD products to compare monthly mean AOD values before and during the war. By examining the spatial-temporal distribution of AOD in 2022 and comparing it with a baseline period from 2012 to 2021, we aim to assess the impact of the conflict. Our analysis employs a time series algorithm that decomposes long-term trends and seasonal variations, enabling us to identify AOD changes associated with the war-induced artificial perturbations. Additionally, we utilize satellite-based tropospheric NO2 data and nighttime lighting data as auxiliary sources to support the analysis of abnormal AOD changes resulting from the war. Furthermore, four parameters from Aerosol Robotic Network (AERONET) mea-surements in the Kyiv site, including angstrom exponent (AE), single scattering albedo (SSA), refractive index (RI), fine mode fraction (FMF) were exclusively discussed to explore the possible changes of aerosol physical-optical properties over Ukraine during the war. Results showed that air quality in Ukraine has been affected by the war in contradictory ways at different levels. At the national level, atmospheric pollution has dropped across Ukraine due to a decrease in the sources of air pollution emissions as a result of the suppression of economic and agricultural activities. Meanwhile, atmospheric air quality has deteriorated at the local scale where war is intense due to the large amounts of air pollutants emitted by explosions. Specifically, a significant decrease in AOD of 22.46% compared to the baseline period was observed across Ukraine in January and February
The increasing demand for unconventional oil and gas resources, especially oil shale, has highlighted the urgent need to develop rapid and accurate strata characterization methods. This paper is the first case and exa...
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