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.

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.

Application of a Bayesian Network Complex System Model Examining the Importance of Customer-Industry Engagement to Peak Electricity Demand Reduction

This paper explores the importance of customer-industry engagement (CIE) to peak energy demand by means of a newly developed Bayesian Network (BN) complex systems model entitled the Residential Electricity Peak Demand Model (REPDM). The REPDM is based on a multi-disciplinary perspective designed to solve the complex problem of residential peak energy demand. The model provides a way to conceptualise and understand the factors that shift and reduce consumer demand in peak times. To gain insight into the importance of customer-industry engagement in affecting residential peak demand, this research investigates intervention impacts and major influences through testing five scenarios using different levels of customer-industry engagement activities. Scenario testing of the model outlines the dependencies between the customer-industry engagement interventions and the probabilities that are estimated to govern the dependencies that influence peak demand. The output from the model shows that there can be a strong interaction between the level of CIE activities and interventions. The influence of CIE activity can increase public and householder support for peak reduction and the model shows how the economic, technical and social interventions can achieve greater peak demand reductions when well-designed with appropriate levels of CIE activities.

Priority of Factors Affected on Customer＇s Satisfaction in the E-Banking by Using Kano Model and Analytical Hierarchy Process： A Case of Iranian Commercial Bank

The aim of the article is to determine the extent to which customer satisfaction＇s in the e-banking in Semnan area had organizational and customer readiness for developing their services. One of the most important sectors that plays key role for grasping developed condition is banking sector. Banks like other institutions also look for augmenting their profits and increasing their strength by expansion. The designing of bank must involve selection of those that have sufficient success potential. Hence, from several factors of success, the following three criteria factors have been： selected-customer satisfied, one dimensional, and product fully functional. These factors offers three question multi criteria group extracted from a 16 norms. Also, three criteria factors have been studied over a period of five years and important criteria for evaluating the norms. The Analytical Hierarchy Process （AHP） has been employed to calculate the success potential of each norm. The empirical data comprises the longitudinal survey of the agricultural banking of the Semnan province. The paper, also, finds that product fully functional is placed as the first priority.

Customized High-speed EMU Design Practice for Jakarta-Bandung HSR

The high-speed EMUs for Jakarta-Bandung high-speed railway(HSR)represent an important image and symbol of the Jakarta-Bandung HSR Project.By relying on the technical platform of the model CR400 EMU,the EMU is upgraded for the customized design in terms of adaptability to geographical environment and track conditions,integration of Indonesian cultural characteristics,etc.In the course of development,in order to accurately grasp the boundary conditions and solve matching adaptation problems,studies are conducted on the exploration of design boundary and the related special technology.With the systematic analysis and design experience summary of the high-speed EMUs for Jakarta-Bandung HSR,the paper aims to provide reference for the O&M of high-speed EMUs for Jakarta-Bandung HSR and the other similar overseas HSR projects.

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.

Exploring a Deep Analysis Method for “Click-Stream” Information from the Perspective of the Flow of Bidirectional Value of Customer Relations Based on Ricoeur's Hermeneutic Theory

Click-streams of online shopping are the tracks/trails of interactions between a customer and a vendor.We observe that it is of great importance both in theory and practice to explore a deep analysis method for analyzing click-stream information of an individual customer in a specific transaction for understanding the bidirectional value transfer within the machine-human interaction of an online store and for its personalization.We analyze the significance,the hierarchical structure and the characteristics of click-stream information and propose that Ricoeur's hermeneutic theory be the foundation of forming such a deep analysis method.Then we use the empirical context information of the click-stream to improve the naive interpretation put forward by Ricoeur.Moreover,we apply the Grounded Theory to extend the deep analysis of Ricoeur's theory of textual interpretation.The improved theory fits well with the needs of interpretation and the analysis of click-stream information.We exemplify and show the feasibility of this analysis method by using data collected(a single case)from a large study of human-computer interaction.

Customer Retention: Behaviour Perspective Model of Ghanaian Telecommunication Industry Using Multinomial Regression Analysis

To stay competitive, the mobile telecommunication companies spend millions of Ghana cedi each year on building long-term relationships with their customers. Marketing managers are constantly challenged with the problem of where to channel the limited resources in order to retain existing customers. This study approaches the customer retention problem in the mobile phone sector from a behavioural perspective, applying the Behavioural Perspective Model as the main analytical framework and further exploits some other factors that influence customer retention. The model includes a set of pre-behaviour and post-behaviour factors to study consumer choice, and explains its relevant drivers in a viable and comprehensive way, grounded in radical behaviourism. Data for the analysis were collected from tertiary students from Accra and Takoradi. Data collected were analysed using the multinomial regression technique. Analysis of the data revealed that the Behaviour setting factor is the only significant element in Behaviour Perspective Model. Further exploitation of behaviour situation revealed that the number of networks a customer uses, previous experience of a customer and customer’s intention are significant factors in determining customer retention in Ghana’s mobile telecommunication industry.

Methodology for Obtaining Electricity-Price Patterns in Customer Response Programs

The main objective of electricity regulators when establishing electricity markets is to decrease the cost of electricity through competition. However, this scenario cannot be achieved without a full participation of the electricity demand by reacting against electricity prices. The aim of this research is to develop tools for helping customers and aggregators to join price and demand response programs, while helping them to hedge against the risk of short-term price volatility. In this way, the capacity of and hybrid methodology （Self-Organizing Maps and Statistical Ward＇s Linkage） to classify high electricity market prices is analysed. Besides, with the help of Non-Parametric Estimation, some price-patterns were found in the abovementioned clusters. The contained knowledge within these patterns supplies customer market-based information on which to base its energy use decisions. The interest for this participation of customers in markets is growing in developed countries to obtain a higher elasticity in demand. Results show the capability of this approach to improve data management and select coherent policies to accomplish cleared demand offers amongst different price scenarios in a more flexible way.

The Relationship between Customer Knowledge Management and Performance of Agricultural Product Innovation

This paper takes an overview of the CKM and the performance of agricultural product innovation from contents of agricultural product innovation and customer knowledge management (CKM) ,the relation between CKM and agricultural product innovation. On the basis of the overview, it builds the theoretical framework of CKM and agricultural product innovation. It points out that enterprises can satisfy demands of customers through acquisition,share,utilization and innovation of customer knowledge,and improve performance of agricultural product innovation through speeding up agricultural product innovation.

Research on customer-oriented product configuration technology of aircraft

Due to the defects of current aircraft product configuration technology, such as the gap between product design and cus- tomers＇ requirements, the low configuration efficiency and etc. a customer-oriented product configuration solution of aircraft was proposed in this paper. Basing on a deep investigation into the market and the structure of the aircraft, this paper proposed a method of dividing and creating the aircraft options, in which we set up optional constraints to meet the demand of configuration and then optimized the constraint algorithm. This work can help to realize the optimum association between the aircraft options and modules. Basing on a research on customer demand, The paper established a customer demand model and a mapping relationship which exists between customer demand and aircraft options, It can also help to make a great contribution to build customer personalized demand of the aircraft configuration orocess and the aircraft confimiration library.

U.S.Cotton Industry Continuing Dialogue on Quality with No.1 Customer

MEMPHIS-A National Cotton Council delegation traveling to Beijing on June 19-30 will make a number of visits with key Chinese officials to:1)provide updates on the U.S. cotton industry’s efforts to improve its cotton quality and 2) ascertain its Chinese textile customers’needs.

Soft Computing of Biochemical Oxygen Demand Using an Improved T–S Fuzzy Neural Network

It is difficult to measure the online values of biochemical oxygen demand(BOD) due to the characteristics of nonlinear dynamics, large lag and uncertainty in wastewater treatment process. In this paper, based on the knowledge representation ability and learning capability, an improved T–S fuzzy neural network(TSFNN) is introduced to predict BOD values by the soft computing method. In this improved TSFNN, a K-means clustering is used to initialize the structure of TSFNN, including the number of fuzzy rules and parameters of membership function. For training TSFNN, a gradient descent method with the momentum item is used to adjust antecedent parameters and consequent parameters. This improved TSFNN is applied to predict the BOD values in effluent of the wastewater treatment process. The simulation results show that the TSFNN with K-means clustering algorithm can measure the BOD values accurately. The algorithm presents better approximation performance than some other methods.

Grey Incidence Analysis Applied to Civil Aircraft Customization Process

The airlines need to select the optional equipment according to their individual development demands and the manufacture′s standard specification manual when purchasing a new airplane.For this customization process,the selection theory is mainly based on qualitative analysis and quantitative analysis.The grey incidence analysis(GIA)is used for modeling,which evaluates the correlations between optional equipment and airlines′individual demands.Meanwhile,the customization demands are quantitatively processed as different weights in evaluation index system with analytical hierarchy process.Then,the value of grey incidence degree is obtained which shows whether the optional equipment is on the purchasing list or not.Finally,two airlines′customization demands are applied in the example of aircraft cabin′s seats,so two different purchasing priorities and equipment installation lists can be obtained.The results and comparisons verify the reasonable of modeling,which provides an objective scheme of aircraft equipment selection.

Customization Product Design Based on User's Emotion and Needs

The paper presents a design method that ensures the ingenuity of the product form as well as the whole and exact expression of user’s needs. The key idea is to establish an automatic design system which can transform the user’s language needs into the product features in real-time. A rifle was taken as a research instance and soldiers were chosen as evaluation customers. The theory of fuzzy set and semantic difference are adopted to evaluate the relationship between user’s needs and product features as well as their alternatives. FAHP (fuzzy analytic hierarchy process) is utilized to judge the user’s satisfactory forms. This method can also be applied to other product form designs.

Cotton's Water Demand and Water-Saving Benefits under Drip Irrigation with Plastic Film Mulch

The primary purpose of this research was to give suitable irrigation program according to the growth period and water requirement.A cotton field experiment with mulched drip irrigation was conducted at the National Field Observation and Research Station for Oasis Farmland Ecosystem in Aksu of Xinjiang in 2008.Water balance method was adopted to study the water requirement and water consumption law of cotton under mulched drip irrigation in Tarim Irrigated Area.Statistical analysis of experimental data of irrigation indicates that the relationship between yield of cotton and irrigation presents a quadratic parabola.We fit the model of cotton water production on the basis of field experimental data of cotton.And the analysis on water saving benefit of cotton under mulched drip irrigation was done.Results indicate that water requirements for the irrigated cotton are 543 mm in Tarim Irrigated Area.The water requirements of seedling stage is 252 mm,budding stage is 186 mm,bolling stage is 316 mm and wadding stage is 139 mm.the irrigation amount determines the spatial distribution of soil moisture and water consumption during cotton life cycle.However,water consumption at different growth stages was inconsistent with irrigation.Quantitatively,the water consumed by cotton decreases upon the increase of irrigation amount.From the perspective of water saving,the maximal water use efficiency can reach 3 091 m3/ha.But the highest cotton yield needs 3464 m3/ha irrigation water.In summary,compared to the conventional drip irrigation,a number of benefits in water saving and yield increase were observed when using plastic mulch.At the same amount of irrigation,the cotton yield with plastic mulch was 30.2% higher than conventional approaches,and the efficiency of water utilization increased by30.2%.While at the same yield level,29.3% water was saved by using plastic mulch,and the efficiency increased by 41.5%.

PROVISIONS OF THE CUSTOMS OF THE PEOPLE’S REPUBLIC OF CHINA ON EXTERNAL AUDIT AND CERTIFICATE OF EXTERNAL AUDIT ISSUED RECENTLY BY THE GENERAL ADMINISTRATION OF CUSTOMS OF THE PEOPLE’S REPUBLIC OF CHINA

In accordance with the regulations as stipulated in the Pro-visions of the Customs of the People’s Republic of China on Ex-ternal Audit, the Customs officers engaged in external audit shalluse the Certificate of External Audit of the Customs (hereinafterreferred to as Certificate) as of June 5, 1997. The Certificate has ablack leather outer covering and is inlaid inside with a pierced andguilded customs emblem, which consists of the red national em-blem in its upper part, and a key and a truncheon encircled by earsof wheat in its lower part. Put in a leather covering, the Certificateis a card sealed up with plastics, on which there is a bareheadedcolour photo of the holder in the Customs uniform and with a

Clustering-based Demand Response for Intelligent Energy Management in 6G-enabled Smart Grids

As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-demand mismatches.How-ever,existing literatures try to adjust customers’load profiles optimally,instead of electricity overhead,energy consumption patterns of residential appliances,customer satisfaction levels,and energy consumption habits.In this paper,a novel DR method is investigated by mixing the aforementioned factors,where the residential customer cluster is proposed to enhance the performance.Clustering approaches are leveraged to study the electricity consumption habits of various customers by extracting their features and characteristics from historical data.Based on the extracted information,the residential appliances can be scheduled effectively and flexibly.Moreover,we propose and study an efficient optimization framework to obtain the optimal scheduling solution by using clustering and deep learning methods.Extensive simulation experiments are conducted with real-world traces.Numerical results show that the proposed DR method and optimization framework outperform other baseline schemes in terms of the system overhead and peak-to-average ratio(PAR).The impact of various factors on the system utility is further analyzed,which provides useful insights on improving the efficiency of the DR strategy.With the achievement of efficient and intelligent energy management,the proposed method also promotes the realization of China’s carbon peaking and carbon neutrality goals.