With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty r...With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty recurrence monitoring and agricultural product sales systems can effectively enhance precise identification and early warning capabilities,promoting the sustainable development of rural economies.This paper explores the application of big data technology in poverty recurrence monitoring,analyzes its innovative integration with agricultural product sales systems,and proposes an intelligent monitoring and sales platform model based on big data,aiming to provide a reference for relevant policy formulation.展开更多
The pharmaceutical industry is facing challenges due to various factors such as supply chain disruptions,changing consumer behavior,and regulatory changes.Accurate demand forecasting is essential to ensure an adequate...The pharmaceutical industry is facing challenges due to various factors such as supply chain disruptions,changing consumer behavior,and regulatory changes.Accurate demand forecasting is essential to ensure an adequate supply of drugs.The goal of this work is to forecast paracetamol product demand.For this purpose,we propose a hybrid forecasting model combining two effective forecasting techniques:SARIMA(Seasonal AutoRegressive Integrated Moving Average)and ANFIS(Adaptive Neuro-Fuzzy Inference System).This proposal consists of nonlinear components of time series by ANFIS and adjusting the result by the mean of the residuals of the SARIMA to improve the accuracy and performance of ANFIS predictions.Before the prediction phase,we preprocess our data and detect the anomalies in our dataset with Locally Selective Combination in Parallel Outlier Ensembles(LSCP).Then,by treating these anomalies as missing values,they are imputed using the combination of fuzzy-possibilistic c-means(FCM)with support vector regression(SVR)and a genetic algorithm(GA).Finally,we evaluate the performance of the model and some known models based on MAPE.We choose the hybrid model SARIMA-ANFIS that provides the most accurate and reliable forecasting.展开更多
With the rapid advancement of human economic levels and modern civilization,the automobile manufacturing industry is increasingly confronted with challenges related to energy scarcity and environmental pollution.Low c...With the rapid advancement of human economic levels and modern civilization,the automobile manufacturing industry is increasingly confronted with challenges related to energy scarcity and environmental pollution.Low carbon emissions and energy savings have become the main focus of automotive development.Under the influence of government incentives,the sales of household electric vehicles(EVs)have increased significantly,although they still represent a small share of the overall car market.To examine the factors influencing consumer purchases of household EVs,this report integrates both qualitative and quantitative analyses,controlling for single variables.Using linear regression,an empirical analysis was conducted on 18 BYD models with varying ranges and prices.The results indicate a strong positive correlation between driving range,selling price,and EV sales.Looking ahead,the development of new energy vehicles should prioritize longer ranges,high-quality features,and cost-effective performance.展开更多
Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensa...Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.展开更多
In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreami...In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.展开更多
This article explores the impact of the three-dimensional cultivation mode on the development of the Suzhou tea industry,focusing on the diversified estimation of the value of output per acre and sales mode.It introdu...This article explores the impact of the three-dimensional cultivation mode on the development of the Suzhou tea industry,focusing on the diversified estimation of the value of output per acre and sales mode.It introduces the history and traditional cultivation practices of tea in Suzhou,as well as the current challenges and problems faced by the industry.An in-depth analysis was conducted on the overview and improvement plans of the three-dimensional cultivation mode,covering relevant technical methods.Based on this analysis,the impact of the three-dimensional cultivation on the value of output per acre was studied and predicted.Its potential and advantages were explored and compared with the effectiveness of traditional cultivation models.Additionally,the impact of the three-dimensional cultivation mode on sales was analyzed,examining its market adaptability and competitiveness,as well as its advantages in expanding sales channels and market coverage.The study also focused on the promoting effect of diversified sales models on the Suzhou tea industry,including direct consumption market development,tea processing product development and promotion,and the integration of tea culture and the tourism industry.To ensure sustainable development,the article evaluates the environmental impact,economic feasibility,social benefits,and farmer benefits of the three-dimensional cultivation model.Finally,the prospects for the development of the Suzhou tea industry were discussed,and the positioning and response strategies of the threedimensional cultivation model were proposed.展开更多
Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This...Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This study aims to address this issue by incorporating machine learning (ML) techniques to improve forecasting accuracy and responsiveness to market changes. The methodology involves gathering extensive sales data and carefully preprocessing it to ensure quality. Various ML algorithms, such as time series analysis, regression models, and neural networks, are utilized to account for the complex and non-linear nature of sales patterns. These models are trained and validated using historical sales data, taking into consideration external factors like economic indicators and consumer trends. The results show a significant enhancement in forecast accuracy compared to traditional methods. The ML models effectively capture underlying trends and seasonal variations, providing reliable predictions that closely match actual sales results. Additionally, the models demonstrate strong adaptability, quickly adjusting to unexpected market shifts.展开更多
UK manufacturers experienced a challenging start to 2024,with sales in the first quarter(Q1)down 10 per cent on the previous quarter,according to a report by Unleashed.However,year-on-year growth showed a modest incre...UK manufacturers experienced a challenging start to 2024,with sales in the first quarter(Q1)down 10 per cent on the previous quarter,according to a report by Unleashed.However,year-on-year growth showed a modest increase of 2 per cent,reflecting the Bank of England’s assessment of weak growth in the manufacturing sector.展开更多
This paper reports literature review in the field of pharmaceutical marketing emphasizing problems faced by medical representatives. India after globalization and being the second highest populated country has emerged...This paper reports literature review in the field of pharmaceutical marketing emphasizing problems faced by medical representatives. India after globalization and being the second highest populated country has emerged as major pharmaceutical market in the world. Pharmaceutical marketing in India is highly relied on personal relationship between medical representatives and doctors. In the last decade, many foreign companies have entered in Indian market. This has posed highly competitive and challenging work environment for medical representatives. Therefore, it is indispensable to study the challenges faced by medical representatives in this dynamic environment.展开更多
The development of social economy and the adjustment of enterprises themselves have forced enterprises to keep pace with the times in cost management. Facing the opportunities and challenges, enterprises should establ...The development of social economy and the adjustment of enterprises themselves have forced enterprises to keep pace with the times in cost management. Facing the opportunities and challenges, enterprises should establish the correct concept of cost control, formulate effective cost control management system, and implement scientifically and effectively. Only by doing a good job of cost control can an enterprise be in an invincible position in the market competition and ensure its sustainable development.展开更多
The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely af...The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely affected.Therefore,in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience,this study aims to utilize historical sales data for exploring,building sales prediction and recommendation models.A novel data science life-cycle and process model with Recency,Frequency,and Monetary(RFM)analysis method with the combination of various analytics algorithms are utilized in this study for sales prediction and product recommendation through user behavior analytics.RFM analysis method is utilized for segmenting customer levels in the company to identify the importance of each level.For the purchase prediction model,XGBoost and Random Forest machine learning algorithms are used to build prediction models and 5-fold Cross-Validation method is utilized to evaluate their.For the product recommendation model,the association rules theory and Apriori algorithm are used to complete basket analysis and recommend products according to the outcomes.Moreover,some suggestions are proposed for the marketing department according to the outcomes.Overall,the XGBoost model achieved better performance and better accuracy with F1-score around 0.789.The proposed recommendation model provides good recommendation results and sales combinations for improving sales and market responsiveness.Furthermore,it recommend specific products to new customers.This study offered a very practical and useful business transformation case that assists companies in similar situations to transform their business models.展开更多
Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modula...Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.展开更多
Using data from the Economic Advisory Center of the State Information Center(SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions o...Using data from the Economic Advisory Center of the State Information Center(SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions of car sales of different kinds of automakers(foreign automakers, Sino-foreign joint automakers, and Chinese automakers), and then identified spatial clusters using the local Moran's indexes. Location quotient analysis was applied to examine the relative advantage of each type of automaker in the local markets. To explain the variations of car sales across cities, we collected several socioeconomic variables and conducted regression analyses. Further, factor analysis was used to extract independent variables to avoid the problem of multicollinearity. By incorporating a spatial lag or spatial error in the models, we calibrated our spatial regression models to address the spatial dependence problem. The analytical results show that car sales varied significantly across cities in China, and most of the cities with higher car sales were the developed cities. Different automakers exhibit diverse spatial patterns in terms of car sales volume, spatial clusters, and location quotients. The scale and incomes factor were extracted and verified as the two most significant and positive factors that shape the spatial distributions of car sales, and together with the spatial effect, explained most of the variations of car sales across cities.展开更多
Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are ...Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are dependent on the sales volume forecasting in some way. If the sales volume forecasting is sloppily done, then the rest of the budgeting process is largely a waste of time. Therefore, the sales volume forecasting process is a critical one for most businesses, and also a difficult area of management. Most of researches and companies use the statistical methods, regression analysis, or sophisticated computer simulations to analyze the sales volume forecasting. Recently, various prediction Artificial Intelligent (AI) techniques have been proposed in forecasting. Support Vector Regression (SVR) has been applied successfully to solve problems in numerous fields and proved to be a better prediction model. However, the select of appropriate SVR parameters is difficult. Therefore, to improve the accuracy of SVR, a hybrid intelligent support system based on evolutionary computation to solve the difficulties involved with the parameters selection is presented in this research. Genetic Algorithms (GAs) are used to optimize free parameters of SVR. The experimental results indicate that GA-SVR can achieve better forecasting accuracy and performance than traditional SVR and artificial neural network (ANN) prediction models in sales volume forecasting.展开更多
One of the most severe problems affecting the efficient operations of gas pipelines is corrosion caused by black powder. According to the literature, the primary source for the existence of black powder is condensed w...One of the most severe problems affecting the efficient operations of gas pipelines is corrosion caused by black powder. According to the literature, the primary source for the existence of black powder is condensed water. In this case study, the temperature (40°C) of the sales gas is much higher than its dew point (9.24°C). The water is therefore in vapor phase. It is then proposed to remove water vapor from the gas at the entrance of the plant using an adsorption process. The recommended technology is the Layered Bed Temperature-Swing Adsorption (LBTSA) with micro-channels with molecular sieve zeolite 4A and activated alumina as adsorbents. In the case of presence of aerosols that could condense water, it is suggested to utilize a RED (Rare Earth Drum) magnetic separator in order to remove black powder from the gaseous feed.展开更多
The forecast of sales volume trend of fresh vegetables has significant referential function for government dominant departments,producers and consumers.In order to evaluate the e-commerce sales information of fresh ve...The forecast of sales volume trend of fresh vegetables has significant referential function for government dominant departments,producers and consumers.In order to evaluate the e-commerce sales information of fresh vegetables scientifically and accurately,the sales volume information of such four common vegetables as baby cabbage,potatoes,bok choy and tomatoes,from Anhui Jinghui Vegetable E-commerce Co.,Ltd.was selected as the research object to establish the sales trend prediction system.Taking the improved SVR as an example,we introduced the overall architecture,detailed design and function realization of the system.The system can reflect the short-term sales volume trend of fresh vegetables,and also can provide guidance for the realization of e-commerce order-oriented management and scientific production.展开更多
Chinese traditional sales channels are seriously attacked by the new ones. Household appliances industry will realize the specialized divisions of. development, manufacture, sale and services completely. The model of ...Chinese traditional sales channels are seriously attacked by the new ones. Household appliances industry will realize the specialized divisions of. development, manufacture, sale and services completely. The model of sales channel in marketing is set as the core of this research; the merits and demerits of different sales channels are analyzed; the complicated selective relationship and the conflicts among the manufacturer, middlemen, and ultimate consumers, and the solutions to present multi-channels market and the developments of the sales channels are elaborated in an overall view; the opinion that the only way to develop this industry is raised to establish the competitive sales channels. The aim is to let local household appliances industry use the natural merits to build up a suitable channel rapidly and efficiently, and to speed up the self development and oeffection.展开更多
基金2025 College Students’Innovation Training Program“Return to Poverty Monitoring and Agricultural Products Sales System”2024 College Students’Innovation Training Program“Promoting Straw Recycling to Accelerate the Sustainable Development of Agriculture”(202413207010)。
文摘With the advancement of the rural revitalization strategy,preventing poverty recurrence among previously impoverished populations has become a crucial social concern.The application of big data technology in poverty recurrence monitoring and agricultural product sales systems can effectively enhance precise identification and early warning capabilities,promoting the sustainable development of rural economies.This paper explores the application of big data technology in poverty recurrence monitoring,analyzes its innovative integration with agricultural product sales systems,and proposes an intelligent monitoring and sales platform model based on big data,aiming to provide a reference for relevant policy formulation.
文摘The pharmaceutical industry is facing challenges due to various factors such as supply chain disruptions,changing consumer behavior,and regulatory changes.Accurate demand forecasting is essential to ensure an adequate supply of drugs.The goal of this work is to forecast paracetamol product demand.For this purpose,we propose a hybrid forecasting model combining two effective forecasting techniques:SARIMA(Seasonal AutoRegressive Integrated Moving Average)and ANFIS(Adaptive Neuro-Fuzzy Inference System).This proposal consists of nonlinear components of time series by ANFIS and adjusting the result by the mean of the residuals of the SARIMA to improve the accuracy and performance of ANFIS predictions.Before the prediction phase,we preprocess our data and detect the anomalies in our dataset with Locally Selective Combination in Parallel Outlier Ensembles(LSCP).Then,by treating these anomalies as missing values,they are imputed using the combination of fuzzy-possibilistic c-means(FCM)with support vector regression(SVR)and a genetic algorithm(GA).Finally,we evaluate the performance of the model and some known models based on MAPE.We choose the hybrid model SARIMA-ANFIS that provides the most accurate and reliable forecasting.
文摘With the rapid advancement of human economic levels and modern civilization,the automobile manufacturing industry is increasingly confronted with challenges related to energy scarcity and environmental pollution.Low carbon emissions and energy savings have become the main focus of automotive development.Under the influence of government incentives,the sales of household electric vehicles(EVs)have increased significantly,although they still represent a small share of the overall car market.To examine the factors influencing consumer purchases of household EVs,this report integrates both qualitative and quantitative analyses,controlling for single variables.Using linear regression,an empirical analysis was conducted on 18 BYD models with varying ranges and prices.The results indicate a strong positive correlation between driving range,selling price,and EV sales.Looking ahead,the development of new energy vehicles should prioritize longer ranges,high-quality features,and cost-effective performance.
文摘Objective To analyze the improvement of the incentive mechanism of sales personnel in pharmaceutical company A,and to promote the smooth operation and further development of the company in a long term.Methods Compensation incentive,performance appraisal,welfare benefit,training incentive,promotion motivation and enterprise cultural inspiration were explored through questionnaires,telephone interviews and in-person interviews.Results and Conclusion This company’s incentive mechanism has problems in two aspects:Material incentives and spiritual incentives.As to the company’s characteristics and strategic development,the optimization countermeasures of incentive mechanism are proposed from the following three aspects:constructing a reasonable incentive system,establishing an efficient spiritual incentive mechanism,and implementing the dynamic incentive and differentiated incentive simultaneously.
文摘In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.
基金Suzhou Agricultural Vocational and Technical College Young Teachers Research Ability Enhancement Program“Research and Screening of Bacteria for Fermented Beverages of Vice Tea and Loquat Flower”(Project No.QN[2022]01)。
文摘This article explores the impact of the three-dimensional cultivation mode on the development of the Suzhou tea industry,focusing on the diversified estimation of the value of output per acre and sales mode.It introduces the history and traditional cultivation practices of tea in Suzhou,as well as the current challenges and problems faced by the industry.An in-depth analysis was conducted on the overview and improvement plans of the three-dimensional cultivation mode,covering relevant technical methods.Based on this analysis,the impact of the three-dimensional cultivation on the value of output per acre was studied and predicted.Its potential and advantages were explored and compared with the effectiveness of traditional cultivation models.Additionally,the impact of the three-dimensional cultivation mode on sales was analyzed,examining its market adaptability and competitiveness,as well as its advantages in expanding sales channels and market coverage.The study also focused on the promoting effect of diversified sales models on the Suzhou tea industry,including direct consumption market development,tea processing product development and promotion,and the integration of tea culture and the tourism industry.To ensure sustainable development,the article evaluates the environmental impact,economic feasibility,social benefits,and farmer benefits of the three-dimensional cultivation model.Finally,the prospects for the development of the Suzhou tea industry were discussed,and the positioning and response strategies of the threedimensional cultivation model were proposed.
文摘Accurate sales forecasting is essential in the fast-paced world of business for effective strategic planning and resource allocation. However, traditional forecasting methods often lack precision and flexibility. This study aims to address this issue by incorporating machine learning (ML) techniques to improve forecasting accuracy and responsiveness to market changes. The methodology involves gathering extensive sales data and carefully preprocessing it to ensure quality. Various ML algorithms, such as time series analysis, regression models, and neural networks, are utilized to account for the complex and non-linear nature of sales patterns. These models are trained and validated using historical sales data, taking into consideration external factors like economic indicators and consumer trends. The results show a significant enhancement in forecast accuracy compared to traditional methods. The ML models effectively capture underlying trends and seasonal variations, providing reliable predictions that closely match actual sales results. Additionally, the models demonstrate strong adaptability, quickly adjusting to unexpected market shifts.
文摘UK manufacturers experienced a challenging start to 2024,with sales in the first quarter(Q1)down 10 per cent on the previous quarter,according to a report by Unleashed.However,year-on-year growth showed a modest increase of 2 per cent,reflecting the Bank of England’s assessment of weak growth in the manufacturing sector.
文摘This paper reports literature review in the field of pharmaceutical marketing emphasizing problems faced by medical representatives. India after globalization and being the second highest populated country has emerged as major pharmaceutical market in the world. Pharmaceutical marketing in India is highly relied on personal relationship between medical representatives and doctors. In the last decade, many foreign companies have entered in Indian market. This has posed highly competitive and challenging work environment for medical representatives. Therefore, it is indispensable to study the challenges faced by medical representatives in this dynamic environment.
文摘The development of social economy and the adjustment of enterprises themselves have forced enterprises to keep pace with the times in cost management. Facing the opportunities and challenges, enterprises should establish the correct concept of cost control, formulate effective cost control management system, and implement scientifically and effectively. Only by doing a good job of cost control can an enterprise be in an invincible position in the market competition and ensure its sustainable development.
基金This research is funded by the School of Computer Sciences,and Division of Research&Innovation,Universiti Sains Malaysia,Short Term Grant(304/PKOMP/6315435)granted to Pantea Keikhosrokiani.
文摘The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down.The general public has responded to call of the government to stay at home.Offline retail stores have been severely affected.Therefore,in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience,this study aims to utilize historical sales data for exploring,building sales prediction and recommendation models.A novel data science life-cycle and process model with Recency,Frequency,and Monetary(RFM)analysis method with the combination of various analytics algorithms are utilized in this study for sales prediction and product recommendation through user behavior analytics.RFM analysis method is utilized for segmenting customer levels in the company to identify the importance of each level.For the purchase prediction model,XGBoost and Random Forest machine learning algorithms are used to build prediction models and 5-fold Cross-Validation method is utilized to evaluate their.For the product recommendation model,the association rules theory and Apriori algorithm are used to complete basket analysis and recommend products according to the outcomes.Moreover,some suggestions are proposed for the marketing department according to the outcomes.Overall,the XGBoost model achieved better performance and better accuracy with F1-score around 0.789.The proposed recommendation model provides good recommendation results and sales combinations for improving sales and market responsiveness.Furthermore,it recommend specific products to new customers.This study offered a very practical and useful business transformation case that assists companies in similar situations to transform their business models.
基金National Key R&D Program of China(Grant No.2018YFB1701701)Sailing Talent Program+1 种基金Guangdong Provincial Science and Technologies Program of China(Grant No.2017B090922008)Special Grand Grant from Tianjin City Government of China。
文摘Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.
基金Under the auspices of National Natural Science Foundation of China(No.41301143)
文摘Using data from the Economic Advisory Center of the State Information Center(SIC), we examined the spatial patterns of car sales in China at the prefectural level in 2012. We first analyzed the spatial distributions of car sales of different kinds of automakers(foreign automakers, Sino-foreign joint automakers, and Chinese automakers), and then identified spatial clusters using the local Moran's indexes. Location quotient analysis was applied to examine the relative advantage of each type of automaker in the local markets. To explain the variations of car sales across cities, we collected several socioeconomic variables and conducted regression analyses. Further, factor analysis was used to extract independent variables to avoid the problem of multicollinearity. By incorporating a spatial lag or spatial error in the models, we calibrated our spatial regression models to address the spatial dependence problem. The analytical results show that car sales varied significantly across cities in China, and most of the cities with higher car sales were the developed cities. Different automakers exhibit diverse spatial patterns in terms of car sales volume, spatial clusters, and location quotients. The scale and incomes factor were extracted and verified as the two most significant and positive factors that shape the spatial distributions of car sales, and together with the spatial effect, explained most of the variations of car sales across cities.
文摘Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are dependent on the sales volume forecasting in some way. If the sales volume forecasting is sloppily done, then the rest of the budgeting process is largely a waste of time. Therefore, the sales volume forecasting process is a critical one for most businesses, and also a difficult area of management. Most of researches and companies use the statistical methods, regression analysis, or sophisticated computer simulations to analyze the sales volume forecasting. Recently, various prediction Artificial Intelligent (AI) techniques have been proposed in forecasting. Support Vector Regression (SVR) has been applied successfully to solve problems in numerous fields and proved to be a better prediction model. However, the select of appropriate SVR parameters is difficult. Therefore, to improve the accuracy of SVR, a hybrid intelligent support system based on evolutionary computation to solve the difficulties involved with the parameters selection is presented in this research. Genetic Algorithms (GAs) are used to optimize free parameters of SVR. The experimental results indicate that GA-SVR can achieve better forecasting accuracy and performance than traditional SVR and artificial neural network (ANN) prediction models in sales volume forecasting.
文摘One of the most severe problems affecting the efficient operations of gas pipelines is corrosion caused by black powder. According to the literature, the primary source for the existence of black powder is condensed water. In this case study, the temperature (40°C) of the sales gas is much higher than its dew point (9.24°C). The water is therefore in vapor phase. It is then proposed to remove water vapor from the gas at the entrance of the plant using an adsorption process. The recommended technology is the Layered Bed Temperature-Swing Adsorption (LBTSA) with micro-channels with molecular sieve zeolite 4A and activated alumina as adsorbents. In the case of presence of aerosols that could condense water, it is suggested to utilize a RED (Rare Earth Drum) magnetic separator in order to remove black powder from the gaseous feed.
基金Supported by Anhui Provincial Science and Technology Major Project(18030701202)General Project of Anhui Provincial Key Research and Development Program(201904a06020056)。
文摘The forecast of sales volume trend of fresh vegetables has significant referential function for government dominant departments,producers and consumers.In order to evaluate the e-commerce sales information of fresh vegetables scientifically and accurately,the sales volume information of such four common vegetables as baby cabbage,potatoes,bok choy and tomatoes,from Anhui Jinghui Vegetable E-commerce Co.,Ltd.was selected as the research object to establish the sales trend prediction system.Taking the improved SVR as an example,we introduced the overall architecture,detailed design and function realization of the system.The system can reflect the short-term sales volume trend of fresh vegetables,and also can provide guidance for the realization of e-commerce order-oriented management and scientific production.
文摘Chinese traditional sales channels are seriously attacked by the new ones. Household appliances industry will realize the specialized divisions of. development, manufacture, sale and services completely. The model of sales channel in marketing is set as the core of this research; the merits and demerits of different sales channels are analyzed; the complicated selective relationship and the conflicts among the manufacturer, middlemen, and ultimate consumers, and the solutions to present multi-channels market and the developments of the sales channels are elaborated in an overall view; the opinion that the only way to develop this industry is raised to establish the competitive sales channels. The aim is to let local household appliances industry use the natural merits to build up a suitable channel rapidly and efficiently, and to speed up the self development and oeffection.
