Multi-Step Clustering of Smart Meters Time Series:Application to Demand Flexibility Characterization of SME Customers

Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy transition.This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons.Smart meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns separately.The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series data.The intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire population.For the first time,a step function approach is applied to reduce time series dimensionality.Customer attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy usage.In addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined clusters.The application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the results.Further research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditions.

Dynamic Analysis of Customer Demand Based on Intuitionistic Fuzzy Number in Product Planning

To address the fuzziness and variability in determining customer demand importance,a dynamic analysis method based on intuitionistic fuzzy numbers is proposed.First,selected customers use intuitionistic fuzzy numbers to represent the importance of each demand.Then,the preference information is aggregated using customer weights and time period weights through the intuitionistic fuzzy ordered weighted average operator,yielding a dynamic vector of the subjective importance of the demand index.Finally,the feasibility of the proposed method is demonstrated through an application example of a vibrating sorting screen.

CSO to Solve Optimal Demand for TOU Customers in Power Systems

The aim of this research is to study the optimal demand decision for the Taiwan Residents industries through CSO （cat swarm optimization） algorithm. The five formulations of optimal demand are developed to solve optimal contract capacity for TOU （time of use） customer. Results indicated that, the CSO algorithm is highly helpful to Taiwan Residents industries on the optimal demand decision. Also the CSO is superior to PSO （particle swarm optimization） in the fast convergence and better performance to find the global best solution in the same iterations.

不同海域Custom450高强度不锈钢的腐蚀规律研究

目的 研究Custom450钢在青岛、舟山、厦门及三亚等4个海域大气和飞溅环境中的自然腐蚀规律。方法 采用形貌分析、腐蚀速率、点腐蚀深度分析等方法对Custom450钢在上述4个海域大气和飞溅区的腐蚀规律进行研究。结果 Custom450钢在4个海域大气环境的年平均腐蚀速率相当,且未观察到有点蚀现象发生,舟山海域的年平均腐蚀速率最小,为0.001 41 mm/a,三亚海域的年平均腐蚀速率最大,为0.001 54 mm/a。4个海域飞溅区的年平均腐蚀速率范围为0.0021~0.0028mm/a,舟山海域的年平均腐蚀速率为0.002 1 mm/a,平均及最大点腐蚀深度分别为5.7μm和25.99μm,均低于其他3个海域。结论 Custom450钢在4个海域的大气环境暴露1 a后,未发现明显的腐蚀现象,表明该钢短期内在上述4个海域海洋大气环境中具有良好的耐蚀性。在飞溅环境中的腐蚀速率高于大气环境,且有明显的点腐蚀现象发生,钢中未溶的NbC相会促进点腐蚀现象的发生。

Linguistic characteristics of English business advertisements targeted on female customers

Advertisement is not only an effective method of promotion, but an elegant act of planning. Successful English advertisements depend on good command and creative application of English words and sentences and smart use of various rhetorical devices. Based on some examples, this paper discusses the linguistic characteristics of English business advertisements targeted on female customers.

CSI-Model-Based Research on Factors Affecting Rate Satisfaction of Government and Corporate CustomersTaking Special-Line Products as an Example

The rate satisfaction of government and corporate customers,to which telecom companies pay special attention,is an important part of the overall satisfaction of the market segment.Focusing on specialline products and based on interview with experts and literature review,this article builds an effect model comprising four factors affecting the major government and corporate customers' satisfaction with the rate,including cost performance,discount degree,rate communication and bill composition.Besides,employing AMOS and other analytical tools,it reveals significant positive effects of the aforementioned four factors on the customer's rate satisfaction,and arranges them in sequence according to the path coefficient of each influence.Based on quantified results,this article proposes management recommendations to improve the rate satisfaction,providing basis for research on the overall rate satisfaction optimization of government and corporate customers.

Study on Customer Demands for Product Innovation

In order to improve the satisfaction degree of customers’individual demands for products and reduce the risk of the product innovation,the characteristics of customer demands for product innovation are analyzed,and the type and content of customer demands are discussed.Then the framework of customer demands acquisition for product innovation is established.Final- ly,the prototype system of customer demands information acquisition and product customization for product innovation which takes mobile phone as the example is developed successfully.

Study on Customer Demands for Product Innovation

In order to improve the satisfaction degree of customers’ individual demands on products and reduce the risk of the product innovation,the characteristics of customer demands for product innovation are analyzed,and their type and content are discussed. Then the framework of customer demands acquisition for product innovation is established. Finally,the prototype system of customer demands information acquisition and product customization for product innovation which takes mobile phone as the example is developed successfully.

Research on Value Assessment-Based Accurate Identification of Government and Corporate Customers of Telecom Operators

Aiming at discovering target customers,this article establishes the value assessment system for government& corporate customers according to the level,stability and accessibility of customer value.With 137 customers as samples,it builds the government & corporate customer value assessment system through analytic hierarchy process(AHP) and identifies target government &corpora te customers by indicator optimization,model fitting and cluster analysis.All these achievements help accurate identification of high-value government and corporate customers and optimization of resource allocation for customer service.

Influence of Customized Demand Generation as a Strategy to Increase Uptake of Voluntary Counseling and Testing Services amongst Sex Workers in Mumbai and Thane

Background: To demonstrate that customized demand generation leads to increased voluntary HIV counseling and testing (VCT) among Sex Workers (SWs). Methods: FHI 360 Aastha implemented Vivek intervention among SWs in Mumbai and Thane, India using customized demand generation through outreach services for VCT. Program monitoring data and integrated counseling and testing center tracking sheets were used to assess the intervention effect. Results: Higher proportion of registered SWs tested during: 1) Vivek months than other months (17% vs. 5%, p < 0.001);2) Post-initiation non-Vivek months than pre-Vivek months (4.7%, vs. 1.5% p < 0.001). Conclusions: Customized demand generation approach is successful in increasing HIV testing.

O2O Enterprises Should Seize the Needs of Customers

In the fierce market competition,how the survived 020 startups identify the pain points in the domains closely related with people’s daily life in order to look for a way out? When interviewed with China’s Foregin Trade,O2O companies mentioned there are always opportunities in the O2O sector,if you could find the real needs of customers.Focus the target to provide customers what they

Beyond Customer Churn: Generating Personalized Actions to Retain Customers in a Retail Bank by a Recommender System Approach

Customer churn may be a critical issue for banks. The extant literature on statistical and machine learning for customer churn focuses on the problem of correctly predicting that a customer is about to switch bank, while very rarely consid-ers the problem of generating personalized actions to improve the customer retention rate. However, these decisions are at least as critical as the correct identification of customers at risk. The decision of what actions to deliver to what customers is normally left to managers who can only rely upon their knowledge. By looking at the scientific literature on CRM and personalization, this research proposes a number of models which can be used to generate marketing ac-tions, and shows how to integrate them into a model embracing both the analytical prediction of customer churn and the generation of retention actions. The benefits and risks associated with each approach are discussed. The paper also describes a case of application of a predictive model of customer churn in a retail bank where the analysts have also generated a set of personalized actions to retain customers by using one of the approaches presented in the paper, namely by adapting a recommender system approach to the retention problem.

Mining Profitability of Telecommunication Customers Using K-Means Clustering

Data mining is the powerful technique, which can be widely used for discovering the customers’ behaviors as well as customer’s preferences. As a result, it has been widely used in top level companies for evaluating their Customer Relationship Management (CRM) system today. In this study, a new K-means clustering method proposed to evaluate the cluster customers’ profitability in telecommunication industry in Sri Lanka. Furthermore, RFM model mainly used as an input variable for K-means clustering and distortion curve used to identify optimal number of initial clusters. Based on the results, telecommunication customers’ profitability in Sri Lanka mainly categorized into three levels.

Evaluation of the Websites of Logistics Operators by Customers

In this article, the results were presented of research concerning the visual and functional aspects of the websites of three largest logistics operators in Poland. The research was carried out with the participation of the following three groups： institutional customers, individual customers and marketing management students. The article covers an attempt to evaluate cooperation through virtual contacts with the company. The analysis also concerned such issues as information on corporate social responsibility （CSR）, information on job offers and the position of the company on the market.

Scheduling and Outsourcing with Multiple Customers

In this paper, we study a new scheduling and outsourcing model with multiple customers in which jobs can be processed by either in-house machine or outsourcing machine.All processed jobs have to be delivered in batches to their respective customers and each shipment incurs a delivery cost as well as a fixed amount of time. We discuss three commonly used objective functions, analyze their complexity and solve them by dynamic programming algorithms.

Corneal collagen cross-linking in patients with keratoconus from the Dresden protocol to customized solutions:theoretical basis

Keratoconus is an ectatic condition characterized by gradual corneal thinning,corneal protrusion,progressive irregular astigmatism,corneal fibrosis,and visual impairment.The therapeutic options regarding improvement of visual function include glasses or soft contact lenses correction for initial stages,gas-permeable rigid contact lenses,scleral lenses,implantation of intrastromal corneal ring or corneal transplants for most advanced stages.In keratoconus cases showing disease progression corneal collagen crosslinking(CXL)has been proven to be an effective,minimally invasive and safe procedure.CXL consists of a photochemical reaction of corneal collagen by riboflavin stimulation with ultraviolet A radiation,resulting in stromal crosslinks formation.The aim of this review is to carry out an examination of CXL methods based on theoretical basis and mathematical models,from the original Dresden protocol to the most recent developments in the technique,reporting the changes proposed in the last 15y and examining the advantages and disadvantages of the various treatment protocols.Finally,the limits of non-standardized methods and the perspectives offered by a customization of the treatment are highlighted.

Study on Demand Response of Residential Power Customer

In order to optimize the ladder-pricing scheme in Shanghai, we present a multi-objective optimization model (MOOM). To build this model, first we use price elasticity theory;divide the ladder pricing into peak electricity bill and valley electricity bill in the time dimension to model the single-user demand response. Second based on the single-user demand response model, combined with the overall users’ electricity distribution density function, we build an all-users demand response model. The proposed model has two objectives: minimize energy consumption and maximize residents’ satisfaction. Simulation results confirm that the proposed model can optimize the ladder-pricing scheme.

Enhancing customers prevention efforts:An incentive feedback mechanism design

To improve the inefficient prevention caused by customers unwillingness to adopt prevention strategies in health management,an incentive feedback mechanism that is based on game theory and contract design theory is introduced.The conditions for making customers and health maintenance organizations(HMOs)willing to participate in the proposed mechanism are given.A dual nonlinear programming model is used to identify the optimal prevention effort of customers and the pricing strategy of HMOs.Results show that to generate increased benefits,HMOs need to consider cost sharing when customers are not familiar with the proposed health services.When health services are gradually accepted,the cost sharing factor can be gradually reduced.Simulation shows that under random circumstances in which the market reaches a certain size,the proposed method exhibits a positive network externality.Motivated by network externality,HMOs only need to make their customers understand that the larger the number of participants,the greater the utility of each person.Such customers may then spontaneously invite others to purchase insurance.