Green consumption behavior prediction based on fan-shaped search mechanism fruit fly algorithm optimized neural network

Predicting consumption behavior is very important for adjusting supplier production plans and enterprise marketing activities. Conventional statistical methods are unable to accurately predict green consumption behavior because it is characterized by multivariate nonlinear interactions. The paper proposes an optimized fruit fly algorithm (FOA) and extreme learning machine (ELM) model for consumption behavior prediction. First, to address the problem of uneven search direction of FOA leading to insufficient search ability and low efficiency, the paper proposes a sector search mechanism instead of a random search mechanism to improve the global search ability and convergence speed of FOA. Second, to address the issue that the initial weights and hidden layer bias values of the ELM are randomly generated, which affects the learning efficiency and generalization of the ELM, the paper uses an improved FOA to optimize the weights and bias values of ELM for improving the prediction accuracy. Taking the green vegetable consumption behavior of Beijing residents as an example, the results show the optimization of the initial weight and threshold of ELM by the GA, PSO, FOA, and SFOA, the prediction accuracy of the GA-ELM, PSO-ELM, FOA-ELM, and SFOA-ELM models all surpass those of ELM. Compared with BPNN, GRNN, ELM, GA-ELM, PSO-ELM, and FOA-ELM models, the RMSE value of SFOA-ELM was decreased by 9.45%, 8.40%, 11.89%, 5.84%, 2.22%, and 2.69%, respectively. These findings demonstrate the effectiveness of the SFOA-ELM model in green consumption behavior prediction and provide new ideas for the accurate prediction of consumption behaviors of other green products with similar characteristics.     

一种动态加权的LDPC译码方法

为了加快低密度奇偶校验（LDPC）码的译码速度，有效改善LDPC码的译码性能，针对校验节点更新过程中的对数似然比（LLR）值的大小，设计了一种LDPC码的动态加权译码方法。以IEEE 802.16e标准的奇偶校验矩阵为例，根据LLR值的变化规律，利用增长因子和抑制因子对和积译码算法和最小和译码算法进行动态加权。仿真结果显示，基于动态加权的译码方法相对于传统译码方法误码率都有明显改进，译码复杂度也有所降低。     

地方政府债务空间与空间债务——基于地根经济的区位黏性视角

本文从人口流动的区位黏性这一全新视角，将地方政府性债务的李嘉图等价命题纳入新经济地理研究框架进行理论分析。为了进一步揭示理论模型的政策含义，采用空间计量方法验证沿海地区地方政府性债务的局部正相关特征。最优的债务政策取决于经济系统的初始条件，在非对称经济结构已经存在的情况下，单纯建设本地区的基础设施只会降低区域内的交易成本，这对于那些仅着眼于投巨资用于城市“硬件”建设的地方政府来说显然是一叶障目。建议依靠基础设施网络提高区域协同创新能力，培育规模报酬递增的专业化产业集群。     

Effects of scale economies and production seasonality on optimal hub locations: the case of regional fresh produce aggregation

Interest in supporting local and regional food systems is rising and food hubs have attracted considerable attention among Federal, State, and local policymakers. This study explores the problem of endogenous hub location in fresh produce value chains in the Northeastern United States. To overcome limitations in the literature, we incorporate the effects of economies of scale and production seasonality into our models. Three experimental models are designed to examine the effects of alternatively applying yearly, quarterly, and monthly data on model solutions. We explicitly assess how interactions of scale economies and seasonality influence the structure and spatial attributes of an optimal regional produce aggregation hub system. The three models generate marketed different solutions and in many respects they lead to different conclusions about developing local/regional supply chains. The monthly model allows for production seasonality and actual hub operation cycle frequency and thus leads to more efficient hub solution with rich policy implications.     

Using machine learning and big data for efficient forecasting of hotel booking cancellations

Cancellations are a key aspect of hotel revenue management because of their impact on room reservation systems. In fact, very little is known about the reasons that lead customers to cancel, or how it can be avoided. The aim of this paper is to propose a means of enabling the forecasting of hotel booking cancellations using only 13 independent variables, a reduced number in comparison with related research in the area, which in addition coincide with those that are most often requested by customers when they place a reservation. For this matter, machine-learning techniques, among other artificial neural networks optimised with genetic algorithms were applied achieving a cancellation rate of up to 98%. The proposed methodology allows us not only to know about cancellation rates, but also to identify which customer is likely to cancel. This approach would mean organisations could strengthen their action protocols regarding tourist arrivals.     

基于模糊多属性群决策的维护方式选择研究

维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。     

Do satisfying walking and cycling trips result in more future trips with active travel modes? An exploratory study

Previous studies have indicated that travel satisfaction - the experienced emotions during, and cognitive evaluation of, a trip - can be affected by travel mode choice and other trip characteristics. However, as satisfactory trips might improve a person's attitude towards the used mode, persons may be more likely to use that same mode for future trips of the same kind. Hence, a cyclical process between travel mode choice and travel satisfaction might occur. In this paper we begin to analyse this process—using a structural equation modelling approach on cross-sectional data—for people who engage in walking and cycling for leisure trips in the Belgian city of Ghent. The focus on walking and cycling reflects recent studies indicating that active travel is often associated with the highest levels of travel satisfaction. Results of this exploratory analysis offer tentative support for the idea of a cyclical process: the evaluation of walking and cycling trips positively affects the respondents' attitude towards the respective mode, which in turn has a positive effect on choosing that mode.     

An extended likelihood framework for modelling discretely observed credit rating transitions

The estimation of the parameters of a continuous-time Markov chain from discrete-time observations, also known as the embedding problem for Markov chains, plays in particular an important role for the modeling of credit rating transitions. This missing data problem boils down to a latent variable setting and thus, maximum likelihood estimation is usually conducted using the expectation-maximization (EM) algorithm. We illustrate that the EM algorithm is likely to get stuck in local maxima of the likelihood function in this specific problem setting and adapt a stochastic approximation simulated annealing scheme (SASEM) as well as a genetic algorithm (GA) to combat this issue. Above that, our main contribution is to extend our method GA by a rejection sampling scheme, which allows one to derive stochastic monotone maximum likelihood estimates in order to obtain proper (non-crossing) multi-year probabilities of default. We advocate the use of this procedure as direct constrained optimization (of the likelihood function) will not be numerically stable due to the large number of side conditions. Furthermore, the monotonicity constraint enables one to combine structural knowledge of the ordinality of credit ratings with real-life data into a statistical estimator, which has a stabilizing effect on far off-diagonal generator matrix elements. We illustrate our methods by Standard and Poor’s credit rating data as well as a simulation study and benchmark our novel procedure against an already existing smoothing algorithm.     

基于PSO的信息熵数据融合非均匀分簇路由算法

针对无线传感器网络分簇算法中能量分布不均衡导致的"热区"和簇头负载过重问题,提出了一种基于PSO算法优化簇头选举的非均匀分簇算法。在候选簇头选举和竞争半径计算过程中综合考虑节点动态能量、节点密度和节点距基站距离,将网络进行非均匀分簇,并引入PSO算法进行最终簇头选举。根据节点能量、节点密度和距基站距离确定簇间单跳多跳结合的路由规则,选取代价函数小的节点作为下一跳节点。基于节点信息熵确定融合阈值,进行簇内数据融合剔除冗余数据。仿真结果表明,改进算法的数据传输量比EEUC算法和UCRA算法分别提高了20%和10%,提升了数据的融合效率,有效延长了网络生命周期,簇头能量消耗得到均衡,减少了网络能量消耗,网络的整体性能显著优于其他对比算法。     

长江经济带中三角地区农业结构的分析与优化对策

[目的]从宏观、中观和微观3个层面深入分析长江经济带中三角地区湖北、湖南和江西3省的农业产业结构及其各产业差异性和相对优势及其竞争力。[方法]在宏观层面运用了传统的基尼系数分析3个省份历史发展上的地区经济水平差异,判断3个地区经济发展是否存在虹吸效应;从中观层面运用区位熵指数分析法分析区域农业产业结构,从农畜林渔等方面判断各区域产业专业化水平程度;从微观层面运用偏离—份额分析法(SSM)分离出3个地区的各部门产业的优势及其竞争力。[结果]区域内的经济差异变化呈不断增大的趋势,基尼系数不断扩大;湖北的种植业、渔业和农林牧渔服务业,湖南的种植业、林业、畜牧业和农林牧渔服务业,江西的林业、渔业都较中三角地区对应的子产业的区位熵指数高;江西木材和竹加工业和烟草业具有较大的产业竞争优势,湖北的茶叶、水产和瓜果疏菜产业优势明显,湖南地区农业产业综合优势主要在于烟草、水果、肉类以及木材和竹类加工业。[结论]通过比较地区农业产业竞争优势,提出发展地区产业特色,合理布局全域农业产业,提高农产品附加收益,稳固对结构优化的资金支持等对策建议。