The Application of Genetic Algorithms and Multidimensional Distinguishing Model in Forecasting and Evaluating Credits for Mobile Clients

To solve the arrearage problem that puzzled most of the mobile corporations, we propose an approach to forecast and evaluate the credits for mobile clients, devising a method that is of the coalescence of genetic algorithm and multidimensional distinguishing model. In the end of this paper, a result of a testing application in Zhuhai Branch, GMCC was provided. The precision of the forecasting and evaluation of the client’s credit is near 90%. This study is very significant to the mobile communication corporation at all levels. The popularization of the techniques and the result would produce great benefits of both society and economy.

Two-level fuzzy evaluation for classification of credits

In this paper, classification models are used as tools to make final decision. Fuzzy method provides the mathematical tools for quantitative analysis and dealing with ambiguous concepts. Analytic Hierarchy Process (AHP) is used to obtain the weight of each index and enables examiners to visualize the decision process and obtain more reasonable evaluation values to solve some problems. An example is given at the end of this paper.

Relationship Between Agricultural Credits and Agricultural Economy Based on Error Correct Model in Heilongjiang Province

Heilongjiang is a large agriculture province.Problems of agriculture,rural areas and farmers are urgent to be solved.The development of agriculture needs the support of agricultural credits,because finance is the center of agriculture economy.However,the low comparative advantage in agriculture and pursuit of the capital interests which aggravate the conflicts of supply and demand of agricultural funds.Lacking of fund is the main factor that constrains the development of agricultural economy.In order to analyze the economic effect of agricultural credits on agricultural economy,an error correction model was set up to research the relationship between them,which based on the least square methods.Through the study of the contribution from agricultural credits to total value of agricultural out-put,the empirical evidence for developing the rural financial vigorously was provided,in order to promote the agricultura leconomic development.

Optimal Policy for EOQ Model with Two Level of Trade Credits in One Replenishment Cycle

In general, a supplier/retailer frequently offer trade credit to stimulate their respective sales. The main purpose of this paper is to investigate the optimal supplier/retailer’s replenishment decisions under two levels of trade credit policy within the economic order quantity (EOQ) framework. This paper deals with the supplier/retailer’s inventory replenishment problem under two levels of trade credit in one replenishment cycle. A different approach of two levels of trade credit is used, which give more freedom to the supplier/retailer in business. In addition, the easy-to-use procedure is developed to efficiently find the optimal cycle time for the retailer under minimizing annual total relevant cost. Finally, a numerical example is given to illustrate these results.

Contribution of Forest Management Credits in Kyoto Protocol Compliance and Future Perspectives

Article 3 paragraph 3 and paragraph 4 of the Kyoto Protocol （KP） allow parties to use credits from land-based activities for offsetting their emission reduction/limitation target committed in the KP. Forest management （FM） is the dominant activity accounted by Annex I parties of the United Nation Framework Convention on Climate Change in the first commitment period of KP （2008-2012）. Data reported for 2008 and 2009 indicate that over half of the emission reduction target of 24 Annex I parties that expect to use FM removals can be offset by FM credits in the first commitment period. EspeciMly the majority of the emission reduction target of Slovenia, Sweden, Latvia, Finland, Japan, and Croatia may be achieved through FM credits. The total FM CAP as contained in decision 16/CMP.1 in the first commitment period was over-estimated significantly by 50% for all KP parties and 36% for parties that elected FM. Some parties such as Russia, Japan, Italy, Germany, and Switzerland that elected FM activity may benefit largely from the over-estimated CAP. Presuming a significant increase of the harvest rate, the FM reference level （FMRL） for 2013-2020 is only 1/5 of the historical mean value of FM removals even though most parties show an increasing or a steady trend of net removals from 1990 to 2009. As a result Annex I parties would be able to use FM credits in the future that are over 4 times of FM CAP in the first commitment period. This potentiM FM credit would account for 7.7% of total emissions by sources without land use, land-use change and forestry activities （LULUCF） in the base year or 1990, and more Annex I parties would share the ＂benefit＂ from the FMRL accounting approach.

Credits for Conservation

Carbon-neutral liquefied natural gas has a great growth potential in China.THE first carbon-neutral liquefied natural gas(LNG)cargo of China National Offshore Oil Corp.(CNOOC)destined for Hong Kong Special Administrative Region of China was delivered on September 29,2021 to the Dapeng terminal in Guangdong.A key feature of the shipment was that the carbon emissions associated with the entire value chain were offset by way of financing a forest carbon sink project in China’s Jiangxi Province and other projects,according to Zhong Xiang,vice director of the Commercial Business of CNOOC’s Gas Power Co.

Effects of formal credit on pastoral household expense: Evidence from the Qinghai-Xizang Plateau of China

Formal credit is critical in agricultural production,allowing more expenditure and productive input,thereby improving farmers'welfare.In pastoral China,formal financial institutions are gradually increasing.However,a limited understanding remains of how formal credit affects herders'household expenses.Based on a survey of 544 herders from the Qinghai-Xizang Plateau of China,this study adopted the propensity score matching approach to identify the effect of formal credit on herders'total household expenses,daily expenses,and productive expenses.The results found that average age,grassland mortgage,and other variables significantly affected herders'participation in formal credit.Formal credit could significantly improve household expenses,especially productive expenses.A heterogeneity analysis showed that formal credit had a greater impact on the household total expense for those at higher levels of wealth;however,it significantly affected the productive expense of herders at lower wealth levels.Moreover,the mediating effect indicated that formal credit could affect herders'household income,thus influencing their household expenses.Finally,this study suggests that policies should improve herders'accessibility to formal credit.

Credits for Conservation

Carbon-neutral liquefied natural gas has a great growth potential in China The first carbon-neutral liquefied natural gas(LNG)cargo of China National O shore Oil Corp.(CNOOC)destined for Hong Kong Special Administrative Region of China was delivered on September 29,2021 to the Dapeng terminal in Guangdong.

Pricing Catastrophe Options with Credit Risk in a Regime-Switching Model

In this paper,we consider the price of catastrophe options with credit risk in a regime-switching model.We assume that the macroeconomic states are described by a continuous-time Markov chain with a finite state space.By using the measure change technique,we derive the price expressions of catastrophe put options.Moreover,we conduct some numerical analysis to demonstrate how the parameters of the model affect the price of the catastrophe put option.

Micro Credits: A New Turn for "Laid-Offs"

Jia Xiangde just didn’t know what to do when, five years ago, he lost his job at a state-owned chemical factory. He was given mi "unemployment pay" of 200 yuan (US$24.1) per month for his family of seven. "My wile had no job and life was really hard for us," he recalls. "I had thought I would be done for until the government stepped in to help. I got a petty loan from the government, and that has helped me turn a new leaf in life."

Trade credit contracting in a risk-averse supply chain under adverse selection and moral hazard

Trade credit,as an effective tool for integrating and coordinating material,information,and financial flows in supply chain management,is becoming increasingly widespread.We explore how a manufacturer can design optimal trade credit contracts when a risk-averse retailer hides its sales cost information(adverse selection)and selling effort level(moral hazard).We develop incentive models for a risk-averse supply chain when adverse selection and moral hazard coexist,which are then compared with the results under single information asymmetry(moral hazard).Moreover,we analyze the effects of private information and risk-aversion coefficient on contract parameters,selling effort level and the profit or utility of the supply chain.The study shows that when the degree of retailer’s risk aversion is within a certain range,reasonable trade credit contracts designed by the manufacturer can effectively induce the retailer to report its real sales cost and encourage it to exert appropriate effort.Furthermore,we find that the optimal trade credit period,optimal transfer payment,and retailer’s optimal sales effort level under dual information asymmetry are less than those under single information asymmetry.Numerical analysis are conducted to demonstrate the effects of the parameters on decisions and profits.

Evolutionary analysis of green credit and automobile enterprises under the mechanism of dynamic reward and punishment based on government regulation

To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game model of gov-ernment,commercial banks,and automobile enterprises;introduced a dynamic reward and punishment mechanism;and analyzed the development process of the three parties’strategic behavior under the static and dynamic reward and punish-ment mechanism.Vensim PLE was used for numerical simulation analysis.Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism.A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations.Under the dynamic reward and punishment mechan-ism,an increase in the initial probabilities of the three parties can promote the system stability,and the government can im-plement effective supervision by adjusting the upper limit of the reward and punishment intensity.Finally,the implementa-tion of green credit by commercial banks plays a significant role in promoting the green development of automobile enter-prises.

Guidelines Procurement under IBRD Loans and IDA Credits

I. INTRODUCTIONPurpose1.1 The purpose of these Guidelines is to informthose carrying out a project that is financed in wholeor in part by a loan from the International Bank forReconstruction and Development (IBRD) or a creditfrom the International Development Association(IDA), of the arrangements to be made for procur-ing the goods and works (including relatedservices) required for the project. The Loan Agree-ment governs the legal relationships between the Bor-rower and the Bank, and the Guidelines are made ap-plicable to procurement of goods and works for theproject, as provided in the agreement. The rightsand obligations of the Borrower and the providers ofgoods and works for the project are governed by thebidding documents, and by the contracts signed bythe Borrower with the providers of goods and works,and not by these Guidelines or the Loan Agreements.No party other than the parties to the Loan Agree-ment shall derive any rights therefrom or have anyclaim to loan proceeds.

Research on Early Warning of Banking Crises from the Perspective of Credit Structures

The relationship between credit expansion and banking crises is complex and cannot be fully explained by total credit alone.A systematic analysis of the relationship between the amount and structure of total credit and banking crises is important for an objective prediction of the influence of potential financial risks.This paper,drawing on data from 15 selected countries,delves into the power of credit indicators in the early warning of banking crises from the perspectives of industrial structure,sector structure,and term structure of credit.Various machine learning methods were used,including Logistic Regression,Random Forest,Decision Tree,Support Vector Machine(SVM),Bagging,and Boosting models.The empirical findings indicate that credit expansion plays a crucial role in triggering banking crises.However,total credit is better suited for the early warning of short-term banking crises,whereas credit structure is more useful for the early warning of long-term banking crises.Moreover,in an early warning system,identifying key early warning indicators is more meaningful than merely increasing the number of indicators.Machine learning can somewhat enhance the early warning power,but it may not always be robust.Therefore,more attention should be paid to potential systemic banking crises resulting from an imbalance in credit structure while regulating the total credit threshold.

Day-to-Day Market Power and Efficiency in Tradable Mobility Credits

An active transportation and demand management framework focusing on tradable mobility credits(TMC)is integrated into an agent-based modeling and simulation(ABMS)platform.In this framework,it is conceived that an auction market within which mobility credits can be transferred between buyers and sellers is constructed in general.The idea of ABMS is extensively incorporated to mimic system users’daily route choices as well as market-related micro-economical decision making process under TMC circumstance.Users are able to form individual propensities towards available bid/ask choices by reinforcement learning principles.The integrated platform offers a brand new insight view of microscopic aspect of the daily operations of credit transfer market,which has hardly been obtained by prior analytical models.Day-to-day traffic dynamics and market dynamics can be captured.Besides,market MOEs,including convergence,stability,efficiency and relative market powers of buyers and sellers under different market policies are investigated.

A Self-Adapting and Efficient Dandelion Algorithm and Its Application to Feature Selection for Credit Card Fraud Detection

A dandelion algorithm(DA) is a recently developed intelligent optimization algorithm for function optimization problems. Many of its parameters need to be set by experience in DA,which might not be appropriate for all optimization problems. A self-adapting and efficient dandelion algorithm is proposed in this work to lower the number of DA's parameters and simplify DA's structure. Only the normal sowing operator is retained;while the other operators are discarded. An adaptive seeding radius strategy is designed for the core dandelion. The results show that the proposed algorithm achieves better performance on the standard test functions with less time consumption than its competitive peers. In addition, the proposed algorithm is applied to feature selection for credit card fraud detection(CCFD), and the results indicate that it can obtain higher classification and detection performance than the-state-of-the-art methods.

Construction of BDS Spatiotemporal Information Agricultural Product Digital Credit System

Spatiotemporal information,positioning and navigation services have become important elements of new type infrastructure.The rapid development of global digital trade provides a large-scale application scenario for the use of Beidou Navigation Satellite System(BDS)spatiotemporal information to support the certification of origin of agricultural products.The BDS spatiotemporal information agricultural product digital credit system uses such modules as BDS,spatiotemporal information collection,spatiotemporal coding,and spatiotemporal blockchain.It incorporates multi-level joint supervision mechanisms such as government,associations,and users.Starting from the initial production link of agricultural products,it realizes the correspondence and locking of online and offline products,effectively improves the integrity and credibility of information in the production process,finished product quality and circulation process of products,effectively manages the green production and anti-channel conflicts of producers,and provides credible information for consumers,thus realizing the digital credit certification of products.The successful practice of characteristic agricultural products in Yunnan Province has verified the application ability of the BDS spatiotemporal information agricultural product digital credit system.This system has played a significant role in promoting the online and offline locking,credible information,effective supervision and high quality and high price of characteristic agricultural products from the field.The BDS provides services for global digital trade and contributes to the further enhancement of the global application scale of GNSS.

N-Credits from Different Maturing Cowpea Varieties to Carrot in Rotation

Legumes constitute a major component of sustainable cropping systems due to their biological nitrogen fixing potential. A field study was conducted in 2020 and 2021 at Ashanti-Mampong in the forest transition zone of Ghana to quantify nitrogen credits to carrot from early (70 - 75 days) and medium maturing (80 - 85 days) cowpea varieties (Asetenapa and Soronko) respectively, and Obatanpa maize variety as a reference crop. The experimental design was a split plot with five Nitrogen levels (0, 30, 45, 60 and 90 N kg/ha) applied to carrot as sub-plots following the legumes and the maize variety as main plots. NPK (15:15:15) was applied at the rate of 250 kg/ha to provide the nitrogen. The sub-plot treatments (0, 30, 45, 60 and 90 N kg/ha) were planted following the two cowpea varieties and the maize variety as a reference crop. Soronko had the highest number of nodules (176) while Asetenapa had the lowest nodules (55). Nitrogen credit to carrot from the early-maturing cowpea (Asetenapa) was 32 N kg/ha in the first year of incorporation and 18 N kg/ha in the second year after incorporation. N-credit from the medium-maturing cowpea (Soronko) was 18 N kg/ha and 29 N kg/ha in the first and second year after incorporation respectively. Obatanpa maize variety with 0 kg N/ha fertilizer level produced the lowest carrot yield, indicating that the soil amendment increased yields. The species and maturity of legumes are important determinants of their N credit contribution to crops in rotation.

社区同群效应与居民网络消费扩容提质

在百年未有之大变局下,扩内需、促消费已成为推动经济高效循环、满足人民美好生活需要的关键途径。作为人际互动与社会关系构建的关键场所,社区居民所形成的关系网络,不仅能强化居民之间的相互依赖,也能使居民消费行为产生同群效应。社区同群效应的信息传递与知识溢出,在促进居民网络消费扩容提质的同时,可以通过增加网络消费信贷、提升消费等级和降低居民依赖心理,使得低于参考点的居民受到激励,实现网络消费的扩容提质,这一点在男性和银发群体以及处于中小城市和农村地区的居民中表现得更为明显。社区同群效应对居民网络消费所产生的这种积极作用,为建立社区交流机制、设计符合居民需求特点的网络消费信贷体系、树立理性消费观和构建能释放内需动力的消费机制提供了新的实证证据,也丰富了居民消费领域的研究。

课程超市视域下大学英语学分制模块课微认证教学评价模式改革研究

本文探讨了在高等职业教育深化改革背景下,大学英语教学通过课程超市、学分制和微认证等创新评价模式,结合MOODLE平台优化教学质量,促进学生个性化学习及教师专业化发展的实践。文章首先指出传统教学评价的局限性,并介绍了相关政策要求,随后详细阐述了这些创新模式的概念及其应用,特别强调了MOODLE平台在支持微认证评价中的作用。研究结果表明,基于MOODLE的微认证体系显著提升了学生的学习效果和动机,同时为教师提供了数据支持,促进了教学策略的调整。该模式构建了更科学、灵活的教学评价体系,对学生的未来职业发展具有积极影响。