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Artificial Intelligence Methods Applied to Catalytic Cracking Processes

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Big data Mining and analytics 2023年第3期6卷 361-380页

作者： Fan Yang Mao Xu Wenqiang Lei Jiancheng Lv College of Computer Science Sichuan UniversityChengdu 610041China Algorithm and Big data center New Hope Liuhe Co LtdChengdu 610000China. data Intelligence Lab New Hope Liuhe Co LtdChengdu 610000China. College of Computer Science Sichuan UniversityChengdu 610041China.

Fluidic Catalytic Cracking(FCC)is a complex petrochemical process affected by many highly non-linear and interrelated *** yield analysis,flue gas desulfurization prediction,and abnormal condition warning are several key research directions in *** paper will sort out the relevant research results of the existing Artificial Intelligence(AI)algorithms applied to the analysis and optimization of catalytic cracking processes,with a view to providing help for the follow-up *** with the traditional mathematical mechanism method,the AI method can effectively solve the difficulties in FCC process modeling,such as high-dimensional,nonlinear,strong correlation,and large *** methods applied in product yield analysis build models based on massive *** fitting the functional relationship between operating variables and products,the excessive simplification of mechanism model can be avoided,resulting in high model *** methods applied in flue gas desulfurization can be usually divided into two stages:modeling and *** the modeling stage,data-driven methods are often used to build the system model or rule base;In the optimization stage,heuristic search or reinforcement learning methods can be applied to find the optimal operating parameters based on the constructed model or rule *** methods,including data-driven and knowledge-driven algorithms,are widely used in the abnormal condition ***-driven methods have advantages in interpretability and generalization,but disadvantages in construction difficulty and prediction *** the data-driven methods are just the ***,some studies combine these two methods to obtain better results.

关键词： neural networks intelligent optimization algorithm catalytic cracking lumped kinetics

Multiple Architectural Approach for Urban Development Using Wearable IoT Devices: A Combined Machine Learning Approach

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Advances in Internet of Things 2018年第3期8卷 27-38页

作者： Raghu T Mylavarapu Bharadwaja Krishnadev Mylavarapu Regional Development center KPMG LLP Montvale NJ USA Business analytics Lead Department of Analytics PLM COE PDM John Deere Co. Moline IL USA

Machine Learning becomes a part of our life in recent days and everything we do in interlinked with machine learning. As a technocrat, we tried to implement machine learning with Internet of Things (IoT) for better implementation of technology in organizations for security. We designed an sample architecture which will carry the burden of safeguarding the organizational data with IoT using machine learning with an effective manner and in this case we were proposing utilization of cloud computing for better understanding of data storage and retrieval process. Machine learning is used for the prediction models based on which we need to perform high level analysis of data and using IoT we promote authorization mechanism based on which we recognize the appropriate recipient of data and cloud for managing the data services with the three-tier architecture. We present the architecture we are proposing for better utilization of machine learning and IoT with cloud architecture.

关键词： Cloud Computing Machine Learning IoT Authentication Architecture

Bridging open source tools and Geoportals for interactive spatial data analytics

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Geo-Spatial Information Science 2019年第3期22卷 185-192页

作者： Bing She Tao Hu Xinyan Zhu Shuming Bao University of Michigan Ann ArborMIUSA center for Geographical Analysis Harvard UniversityCambridgeMAUSA Geocomputation center for Social Sciences Wuhan UniversityWuhanChina State Key Lab of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Collaborative Innovation center of Geospatial Technology WuhanChina China data Institute Ann ArborMIUSA

Geoportals have been the primary source of spatial information to researchers in diverse *** years have seen a growing trend to integrate spatial analysis and geovisual analytics inside *** could use the Geoportal to conduct basic analysis without offline *** practice,domain-specific analysis often requires researchers to integrate heterogeneous data sources,leverage new statistical models,or build their own customized *** tasks are increasingly being tackled with open source tools in programming languages such as Python or ***,it is unrealistic to incorporate the numerous open source tools in a Geoportal platform for data processing and *** work provides an exploratory effort to bridge Geoportals and open source tools through Python *** Geoportal demonstrated in this work is the Urban and Regional Explorer for China studies.A python package is provided to manipulate this platform in the local programming *** server side of the Geoportal implements a set of service endpoints that allows the package to upload,transform,and process user data and seamlessly integrate them into the existing datasets.A case study is provided that illustrated the use of this package to conduct integrated analyses of search engine data and baseline census *** work attempts a new direction in Geoportal development,which could further promote the transformation of Geoportals into online analytical workbenches.

关键词： Geoportal open source Python web GIS spatial analysis

Smoking, smoking cessation, and survival after cancer diagnosis in 128,423 patients across cancer types

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Cancer Communications 2022年第12期42卷 1421-1424页

作者： Huakang Tu Yuanqing Ye Maosheng Huang Kunlin Xie Wong-Ho Chow Hua Zhao Xifeng Wu Department of Big data in Health Science School of Public Health Center of Clinical Big Data and Analytics of The Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang 310058P.R.China Department of Epidemiology The University of Texas MD Anderson Cancer CenterHoustonTX 77054USA The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province HangzhouZhejiang 310058P.R.China Department of Liver Surgery&Liver Transplantation West China HospitalSichuan UniversityChengduSichuan 610041P.R.China Department of Family Medicine and Population Health Virginia Commonwealth UniversityRichmondVA 23284USA Cancer center Zhejiang UniversityHangzhouZhejiang 310058P.R.China

Dear Editor,Given the systemic and substantial health consequences of smoking and the significant cancer risk from smoking[1,2],it is expected that cancer patients would quit smoking after cancer ***,the smoking rate among cancer survivors is only slightly lower than that among the general population[3,4],and 64%of smokers diagnosed with cancer continued to smoke even after they learned they had cancer[5].In addition,some former smokers may resume smoking after surviving cancer[6].A number of previous studies have investigated the association between smoking and clinical outcomes in cancer patients[1,7–10].Nevertheless,most studies were conducted in smoking-related cancers,and evidence for non-smoking-related cancers is *** is an urgent need for more convincing evidence showing the harms of smoking and the benefits of smoking cessation to promote smoking cessation in cancer patients and *** systematically studied the associations of smoking status,smoking intensity,age at initiation,and smoking cessation at cancer diagnosis with all-cause mortality in a prospective cohort of 128,423 cancer patients across 23 cancer types from the MD Anderson Cancer Patients and Survivors Cohort.

关键词： diagnosis patients smoke

A novel approach to model the role of mobility suppression and vaccinations in containing epidemics in a network of cities

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Infectious Disease modelling 2024年第2期9卷 397-410页

作者： Leen Alrawas Abdessamad Tridane Ghassane Benrhmach Department of Physics New York University Abu DhabiAbu DhabiAbu DhabiUnited Arab Emirates Department of mathematical Sciences United Arab Emirates UniversityAl AinAbu DhabiUnited Arab Emirates Emirates center for Mobility Research United Arab Emirates UniversityAl AinAbu DhabiUnited Arab Emirates Department of Statistics and Business analytics United Arab Emirates UniversityAl AinAbu DhabiUnited Arab Emirates

This paper presents a comprehensive agent-based model for the spread of an infection in a network of *** mobility is defined between each two cities and can take different *** work examines the role that such mobility levels play in containing the infection with various vaccination coverage and age *** results indicate that mobility reduction is sufficient to control the disease under all circumstances and full lockdowns are not a *** has to be reduced to different ratios depending on the vaccination level and age distribution.A key finding is that increasing vaccination coverage above a certain level does not affect the mobility suppression level required to control the infection anymore for the cases of young population and heterogeneous age *** investigating several migration and commuting patterns,it is found that shutting mobility in a few local places is favored against reducing mobility over the entire country *** addition,commuting-and not migration-influences the spread level of the *** work offers an exclusive combined network-based and agent-based model that makes use of randomly generated mobility matrices.

关键词： Agent-based modeling Network Epidemics

Heatwave exacerbates air pollution in China through intertwined climate-energy-environment interactions

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Science Bulletin 2024年第17期69卷 2765-2775页

作者： Tianshu Chen Tao Wang Likun Xue Guy Brasseur Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China Environment Research Institute Shandong UniversityQingdao 266237China Big data Research center for Ecology and Environment Shandong UniversityQingdao 266237China Environmental modelling Group Max Planck Institute for MeteorologyHamburg 20146Germany National center for Atmospheric Research BoulderCO 80307USA

Climate change is increasing the frequency and intensity of heatwaves, raising concerns about their detrimental effects on air quality. However, a role for heatwave-human-environment interactions in air pollution exacerbation has not been established. In the summer of 2022, record-breaking heatwaves struck China and Europe. In this study, we use integrated observational data and machine learning to elucidate the formation mechanism underlying one of the most severe ozone pollution seasons on record in central eastern China, an area that encompasses approximately half of China's total population and sown *** findings reveal that the worsened ozone and nitrogen dioxide pollution resulted from a mismatch between energy demand and supply, which was driven by both heatwaves and energy policy-related factors. The observed adverse heatwave-energy-environment feedback loop highlights the need for the diversification of clean energy sources, more resilient energy structures and power policies, and further emission control to confront the escalating climate challenge in the future.

关键词： Heatwaves Air pollution Ozone Energy Machine learning

Diagnosis of Moist Vorticity and Moist Divergence for a Heavy Precipitation Event in Southwestern China

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Advances in Atmospheric Sciences 2017年第1期34卷 88-100页

作者： Gang LI Daoyong YANG Xiaohua JIANG Jing PAN Yanke TAN Xichang Satellite Launch center Xichang 615000China State key Laboratory at Numerical modelling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Meteorology and Oceanography PLA University of Science and TechnologyNanjing 211101China

A regional heavy precipitation event that occurred over Sichuan Province on 8-9 September 2015 is analyzed based on hourly observed precipitation data obtained from weather stations and NCEP FNL data. Two moist dynamic parameters, i.e., moist vorticity （mζ and moist divergence （mδ）, are used to diagnose this heavy precipitation event. Results show that the topography over southwestern China has a significant impact on the ability of these two parameters to diagnose precipitation. When the impact of topography is weak （i.e., low altitude）, rn（ cannot exactly depict the location of precipitation in the initial stage of the event. Then, as the precipitation develops, its ability to depict the location improves significantly. In particular, m（ coincides best with the location of precipitation during the peak stage of the event. Besides, the evolution of the m（ center shows high consistency with the evolution of the precipitation center. For mδ, although some false-alarm regions are apparent, it reflects the location of precipitation almost entirely during the precipitation event. However, the mδ center shows inconsistency with the precipitation center. These results suggest that both m（ and mδ have a significant ability to predict the location of precipitation. Moreover, m（ has a stronger ability than mδ in terms of predicting the variability of the precipitation center. However, when the impact of topography is strong （i.e., high altitude）, both of these two moist dynamic parameters are unable to depict the location and center of precipitation during the entire precipitation event, suggesting their weak ability to predict precipitation over complex topography.

关键词： moist vorticity moist divergence heavy precipitation southwestern China

Impacts of a Large-scale Adaptive Blending Scheme for CMA-MESO on Regional Forecasts-A Case Study of Typhoon Haima

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Journal of Tropical Meteorology 2021年第4期27卷 330-345页

作者： FENG Jia-li GAO Yan XIA Xin MA Yu-long SUN Jian LI Yuan CHEN Dong-mei WAN Qi-lin Guangdong-Hong Kong-Macao Greater Bay Area Weather Research center for Monitoring Warning and Forecasting/Shenzhen Institute of Meteorological Innovation ShenzhenGuangdong 518045 China CMA Earth System modelling and Prediction Centre China Meteorological AdministrationBeijing 100081 China

Large-scale atmospheric information plays an important role in the regional model for the forecasts of weather such as tropical cyclone(TC).However,it is difficult to be fully represented in regional models due to domain size and a lack of observation data,particularly at sea used in regional data *** analysis has been developed and implemented in regional models to reintroduce large-scale information from global model to regional *** of the impact of this large-scale blending scheme for the Global/Regional Assimilation and PrEdiction System(CMA-MESO)regional model on TC forecasting is limited and this study attempts to further progress by examining the adaptivity of the blending scheme using the two-dimensional Discrete Cosine Transform(2D-DCT)filter on the model forecast of Typhoon Haima over Shenzhen,China in 2016 and considering various cut-off *** showed that the error of the 24-hour typhoon track forecast can be reduced to less than 25 km by applying the scale-dependent blending scheme,indicating that the blending analysis is effectively able to minimise the large-scale bias for the initial *** improvement of the wind forecast is more evident for u-wind component according to the reduced root mean square errors(RMSEs)by comparing the experiments with and without blending ***,the higher equitable threat score(ETS)provided implications that the precipitation prediction skills were increased in the 24h forecast by improving the representation of the large-scale feature in the CMA-MESO ***,significant differences of the track error forecast were found by applying the blending analysis with different cut-off wavelengths from 400 km to 1200 km and the track error can be reduced less than by 10 km with 400 km cut-off wavelength in the first 6h *** highlighted that the blending scheme with dynamic cut-off wavelengths adapted to the development of different TC systems is ne

关键词： blending analysis tropical cyclone track forecast tropical cyclone typhoon large-scale feature regional model

Airline Disruption Management:A Review of Models and Solution Methods

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Engineering 2021年第4期7卷 435-447页

作者： Yi Su Kexin Xie Hongjian Wang Zhe Liang Wanpracha Art Chaovalitwongse Panos M.Pardalos School of Economics and Management Tongji UniversityShanghai 200092China Xiamen Airlines Xiamen 361006China Department of Industrial Engineering and Institute for Advanced data analytics University of ArkansasFayettevilleAR 72701USA center for Applied Optimization Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleFL 32611USA

The normal operation of aircraft and flights can be affected by various unpredictable factors,such as severe weather,airport closure,and corrective maintenance,leading to disruption of the planned *** a disruption occurs,the airline operation control center performs various operations to reassign resources(e.g.,flights,aircraft,and crews)and redistribute passengers to restore the schedule while minimizing *** introduce different sources of disruption and corresponding ***,basic models and recently proposed extensions for aircraft recovery,crew recovery,and integrated recovery are reviewed,with the aim of providing models and methods for different disruption scenarios in the practical implementation of *** addition,we provide suggestions for future research directions in these topics.

关键词： Disruption management Aircraft recovery problem Crew recovery problem Integrated recovery problem