Cotton Incorporated:Color & Surface——Trend Forecast S/S 2011

Daredevil·Gladiator·Cherry Red·Whirlwind·Flash·Grit·Spider Grass·MercuryWith less to lose,we take a risk,creating challenges and pushingourselves in ways we only fantasized about while living in the safezone.Self-tested,defying limits,we feel invigorated.Each stepwe take towards our wildest dreams brings us one step closer tothe edge.This dynamic palette merges bold and muted tones.Itschameleon nature applies from active to formal wear.

SSI9 Trend forecast

Inquisitor Making sense of the static around us,digging deeper permeates every aspect of our lives.Scrutinizing instead of assuming,we are inspired to self-educate which infiltrates everything from our consumer decisions to global perspectives.Self-identification through brands or political movements loses steam as perspective is gained through more unbiased or raw outlets.

Forecast Forecasts the Trend

The latest release of "2009 China Luxury Forecast" shows that while the financial crisis is leading a general decline in demand for luxury brands in Europe,America and Japan,the global economic downturn has had limited impact on Chinese luxury consumption and that there is widespread confidence in the future among Chinese luxury consumers.

The Seasonal Rainfall Forecast in Nanning City in 2019 with the Method of Trend Comparison Ratio (TCR)

In this paper, the monthly rainfall statistical data of Nanning City, Capital of Guangxi Zhuang Autonomous Region, China, from 2006 to 2018, were collected. On the basis of qualitative analysis of the rainfall seasonal changing law, the non-linear seasonal rainfall forecast model on Nanning City with the method of Trend Comparison Ratio (TCR) was established by the statistical analysis software Office Excel 2013. The model was used to predict the rainfall in spring, summer, autumn and winter in Nanning in 2019. The results were: 286.41 mm, 695.79 mm, 292.20 mm and 118.11 mm, respectively. It was also found that the predicted results were consistent with the seasonal distribution characteristics, annual distribution characteristics and the trend of historical rainfall time series fluctuation, through the qualitative analysis of figures. Compared with the actual measured rainfall data of Nanning City in 2019 in the China Statistical Yearbook (2020), the predicted values are basically consistent with the measured values.

1990—2021年中国归因于饮食因素的缺血性心脏病疾病负担变化趋势及预测研究

背景缺血性心脏病(IHD)是导致中国居民疾病负担的第二大原因,饮食因素干预被认为是减少疾病负担有效及可行的措施。目的分析1990—2021年中国归因于饮食因素的IHD疾病负担变化及未来变化趋势,以期为中国IHD的饮食防治提供参考。方法提取2021年全球疾病负担(GBD 2021)数据库中1990—2021年中国、全球、不同社会人口指数(SDI)地区的归因于饮食因素的IHD疾病负担相关数据,应用Joinpoint模型计算年度变化百分比(APC)及平均年度变化百分比(AAPC),分析1990—2021年中国、全球、不同SDI地区归因于饮食因素的IHD疾病负担,中国不同性别、年龄人群归因于饮食因素的IHD疾病负担以及归因于不同类型饮食因素的IHD疾病负担。利用贝叶斯年龄时期队列(BAPC)模型预测2022—2031年中国归因于饮食因素的IHD标化死亡率、标化伤残调整寿命年(DALY)率变化趋势。结果2021年中国归因于饮食因素的IHD标化死亡率为44.26/10万、标化DALY率为820.87/10万,与全球水平接近,高于高SDI地区,低于其余4类SDI地区。1990—2021年中国归因于饮食因素的IHD标化死亡率(AAPC=-0.17%,P<0.001)、标化DALY率(AAPC=-0.50%,P<0.001)与全球及五类SDI地区一致,均呈现下降趋势,全球下降幅度明显高于中国,高SDI地区下降速度最快。1990年与2021年中国男性归因于饮食因素的IHD疾病负担均高于女性;1990—2021年中国男性归因于饮食因素的IHD标化死亡率(AAPC=0.25%,P<0.001)呈上升趋势,女性标化死亡率(AAPC=-0.71%,P<0.001)、标化DALY率(AAPC=-1.23%,P<0.001)均呈下降趋势。1990与2021年中国归因于饮食因素的IHD疾病负担随着年龄增长呈上升趋势,≥70岁人群的死亡率、DALY率最高;1990—2021年50~69岁人群死亡率、DALY率呈下降趋势,而15~49岁、≥70岁人群呈上升趋势(P<0.001)。1990年与2021年归因于13种饮食因素的IHD标化死亡率、标化DALY率排名前两位的饮食因素均是钠摄入过量、全谷物摄入不足;1990—2021年标化死亡率、标化DALY率上升趋势较明显的是含糖饮料摄入过量、加工肉摄入过量、红肉摄入过量。BAPC模型显示,未来10年中国归因于饮食因素的IHD标化死亡率,标化DALY率均呈下降趋势。结论1990—2021年中国归因于饮食因素的IHD标化死亡率、标化DALY率均呈下降趋势,但下降速度与高SDI地区相比差距较大,男性和老年人群负担较重,因此仍需重视IHD的饮食防控策略,加强宣传健康的膳食模式,倡导增加全谷物的摄入,减少钠盐、含糖饮料、加工肉、红肉的摄入,采取针对性措施进行有效干预以减轻其疾病负担。

Fashion Color Forecasting by Applying an Improved Back Propagation Neural Network

Fashion color forecasting is one of the most important factors for fashion marketing and manufacturing. Several models have been applied by previous researchers to conduct fashion color forecasting. However, few convincing forecasting systems have been established. A prediction model for fashion color forecasting was established by applying an improved back propagation neural network (BPNN) model in this paper. Successive six-year fashion color palettes, released by INTERCOLOR, were used as learning information for the neural network to develop a reliable prediction model. Colors in the palettes were quantified by PANTONE color system. Additionally, performance of the established model was compared with other GM(1, 1) models. Results show that the improved BPNN model is suitable to predict future fashion color trend.

Research on trend prediction of component stock in fuzzy time series based on deep forest

With the continuous development of machine learning and the increasing complexity of financial data analysis,it is more popular to use models in the field of machine learning to solve the hot and difficult problems in the financial industry.To improve the effectiveness of stock trend prediction and solve the problems in time series data processing,this paper combines the fuzzy affiliation function with stock-related technical indicators to obtain nominal data that can widely reflect the constituent stocks in the case of time series changes by analysing the S&P 500 index.Meanwhile,in order to optimise the current machine learning algorithm in which the setting and adjustment of hyperparameters rely too much on empirical knowledge,this paper combines the deep forest model to train the stock data separately.The experimental results show that(1)the accuracy of the extreme random forest and the accuracy of the multi-grain cascade forest are both higher than that of the gated recurrent unit(GRU)model when the un-fuzzy index-adjusted dataset is used as features for input,(2)the accuracy of the extreme random forest and the accuracy of the multigranular cascade forest are improved by using the fuzzy index-adjusted dataset as features for input,(3)the accuracy of the fuzzy index-adjusted dataset as features for inputting the extreme random forest is improved by 18.89% compared to that of the un-fuzzy index-adjusted dataset as features for inputting the extreme random forest and(4)the average accuracy of the fuzzy index-adjusted dataset as features for inputting multi-grain cascade forest increased by 5.67%.

FORECAST模型的原理、方法和应用

数学模型是一个重要的工具,可以很好地帮助科学家和政府决策人员进行规划和预测。最近几十年来,数学模型、经验模型和基于过程的计算机模型的大量涌现,为现代生态学的发展做出了巨大的贡献。其中森林生态系统过程模型就是一类非常重要的林业模型。FORECAST模型,是一个基于森林生态系统过程的林分水平模型。它可以模拟多种管理策略对森林的影响,而且能够预测森林生态系统结构和功能的未来发展趋势,帮助我们制定合适的管理策略,为森林生态系统的优化管理服务。主要从FORECAST模型的发展概况、原理、方法和实际应用,并针对目前该模型的优势和局限性进行了简介。

Unveiling Global Human Trafficking Trends: A Comprehensive Analysis

This paper presents a comprehensive analysis of global human trafficking trends over a twenty-year period, leveraging a robust dataset from the Counter Trafficking Data Collaborative (CTDC). The study unfolds in a systematic manner, beginning with a detailed data collection phase, where ethical and legal standards for data usage and privacy are strictly observed. Following collection, the data undergoes a rigorous preprocessing stage, involving cleaning, integration, transformation, and normalization to ensure accuracy and consistency for analysis. The analytical phase employs time-series analysis to delineate historical trends and utilizes predictive modeling to forecast future trajectories of human trafficking using the advanced analytical capabilities of Power BI. A comparative analysis across regions—Africa, the Americas, Asia, and Europe—is conducted to identify and visualize the distribution of human trafficking, dissecting the data by victim demographics, types of exploitation, and duration of victimization. The findings of this study not only offer a descriptive and predictive outlook on trafficking patterns but also provide insights into the regional nuances that influence these trends. The article underscores the prevalence and persistence of human trafficking, identifies factors contributing to its evolution, and discusses the implications for policy and law enforcement. By integrating a methodological approach with quantitative analysis, this research contributes to the strategic planning and resource allocation for combating human trafficking. It highlights the necessity for continued research and international cooperation to effectively address and mitigate this global issue. The implications of this research are significant, offering actionable insights for policymakers, law enforcement, and advocates in the ongoing battle against human trafficking.

Electric Load Forecasting for Shanghai Urban Area

In this paper electric load is forecast for the classified power consumers of Shanghai urban area for the scheduled years in short term and in long term respectively. The monthly load in 1999 is forecast on the basis of the data during 1992～1998, and the approximate load in 2010 is forecast on the basis of the data during 1990～1998.

Runoff of the upper Yellow River above Tangnag: characteristics, evolution and changing trends

Runoff and its evolution, based on hydrometeorological data from surface measurement stations, are analyzed for the upper reaches of the Yellow River above Tangnag. Some mathematical statistical models, for example, Period Extrapolation-Gradual Regression Model, Grey Topology Forecast Model and Box-Jinkins Model, are applied in predicting changing trends on the runoff. The analysis indicates that the runoff volume in the upper Yellow River above Tangnag is ending a period of extended minimum flows. Increasing runoff is expected in the coming years.

A Hybrid Short Term Load Forecasting Model of an Indian Grid

This paper describes an application of combined model of extrapolation and correlation techniques for short term load forecasting of an Indian substation. Here effort has been given to improvise the accuracy of elec-trical load forecasting considering the factors, past data of the load, respective weather condition and finan-cial growth of the people. These factors are derived by curve fitting technique. Then simulation has been conducted using MATLAB tools. Here it has been suggested that consideration of 20 years data for a devel-oping country should be ignored as the development of a country is highly unpredictable. However, the im-portance of the past data should not be ignored. Here, just previous five years data are used to determine the above factors.

Trace Elements in Lake Baikal: Current Status, Forecast and Monitoring Problems

Assessment of the current status of Lake Baikal proved to be based on changes in natural (“preindustrial”) chemical content in basic abiotic and biological compartments of the Lake geosystem. This approach was used to evaluate background “base-line levels” of 6 major and about 50 minor and trace ele-ments in the Lake Baikal water body using a number of most reliable data re-ported within 1992-2012. In terms of environment geochemistry Baikal is one of the purest water reservoirs on the Earth. A simple mass balance model was proposed for assessing possible anthropogenic impact on Baikal water geo-chemistry. Estimations of change trends showed that only for Na+, SO42-, Cl- and Mo growth rate of their average concentrations in the Lake occurred to be 1%, 3%, 7% and 2% in every 10 years. Space-time monitoring schedules for all water body compartments of the Lake are proposed as well as similar moni-toring programs for tributaries, precipitations, bottom sediments, aquatic biota.

电信制造业销售预测精度(forecast accuracy)的趋势分析方法——基于数据仓库技术解决方案的研究

电信制造企业中销售预测精度是用来衡量销售人员的预测水平.在企业日常生产活动中,预测人员要根据可能发生的销售合同进行提前预测.这就要求预测人员对销售需求进行很好的估计和度量.在实际的合同交货月所记录的真实出货记录在ERP系统中.于是预测精度的要求由此而来.预测精度是根据产品的实际销售数量和预测数量进行对比分析得出前一个月对当前月的预测精度.再根据不同的预测月不同的权重进行加权平均得出的实际精度.这种指标的衡量意义在预测人员可以此作为参照不断提高预测水平.生产部门和仓储部门可以进行精确计划和合理安排库存.提高准时交货率和减少库存成本.使得企业的资源得到精确配置.预测精度的趋势分析方式基于以上的计算方法加上趋势分析,对产品,客户,地区进行历史预测数据进行展现.提供一个直观的变动趋势来满足不同的级别管理层的考核需要.进行日常跟踪从而提出改进需要.达到资源的最优配置.从而给企业带来管理成本的下降.

基于SARIMA模型的上海市宝山区2024年水痘流行趋势预测

目的构建模型预测上海市宝山区2024年的水痘发病趋势,为水痘早期预警和有效防控提供科学依据。方法利用宝山区2010—2022年报告水痘个案数据,运用R语言构建季节性自回归滑动平均模型,用2023年数据进行验证,最后用验证模型预测2024年水痘流行趋势。结果宝山区2010—2022年水痘年均发病率为69.67/10万,2020年起发病数和发病率有所降低。宝山区水痘月发病数据为平稳序列,具有明显季节性。ARIMA(1,0,1)(0,1,1)12为最优拟合模型,残差经Ljung-Box检验为白噪声序列。2023年1—12月实际发病数均在预测值的95%可信区间内。预测显示宝山区2024年水痘发病数为762例,全年发病有2个高峰。结论ARIMA(1,0,1)(0,1,1)12模型能较好拟合宝山区水痘的发病趋势,可用于宝山区水痘短期发病情况的预测。

Road Traffic Accident Scenario, Pattern and Forecasting in Bangladesh

The main aim of this research work is to be aware of the road traffic accident scenario, injurious effects and pattern in Bangladesh. Moreover we are interested to forecast the magnitude of road traffic accidents for the future so that decision makers can make appropriate decision for precaution. This study also provides an assessment of road traffic accidents in Bangladesh and its impact based on data collected for the period of 1971 to 2017. In this study we have tried to pick up the main reasons of road accidents and to observe the tremendous situation. The study observed that the general trends of road traffic accident (RTA), deaths and injuries reveal that the number of RTA, deaths and injuries increased gradually with little fluctuations form 1971 to 2007 and after 2007 there is a slow decreasing trend. Although the number of RTA and deaths observed decreasing trend in recent years, the ratio of number of deaths to number of accident increased significantly. The rate of register vehicles per 10,000 people increased moderately throughout the period but a sharp increment is exhibited from 2009. Highest percentage of RTA (34%) and deaths is due to RTA (32%) in Dhaka division while the lowest percentage of RTA (4%) in Barisal and Sylhet divisions and deaths is due to RTA (3%) in Barisal division. It is noticed that the maximum number of injuries occurred between ages 21 and 30 while the maximum number of deaths occurred between ages 11 and 30. Most of the RTA and deaths due to RTA are caused by run over by vehicles and head to head collision. The severity of occurring road accident and number of deaths are higher during the festive periods because of involving higher frequency of traveling than usual. The time plot shows that the graph maintains a decreasing movement from 2012 to 2015 but increases from 2015 to 2017. In the research an additive time series model approach is applied. It included the estimation of trend, seasonal variation and random variation using triple exponential smoothing method. We performed forecasting of RTA eliminating seasonal impact for the next three consecutive years (2018-2020) with 95% confidence interval using Holt-Winters exponential technique.

Skillful Seasonal Forecasts of Summer Surface Air Temperature in Western China by Global Seasonal Forecast System Version 5

Variations of surface air temperature （SAT） are key in affecting the hydrological cycle, ecosystems and agriculture in western China in summer. This study assesses the seasonal forecast skill and reliability of SAT in western China, using the GloSea5 operational forecast system from the UK Met Office. Useful predictions are demonstrated, with considerable skill over most regions of western China. The temporal correlation coefficients of SAT between model predictions and observations axe larger than 0.6, in both northwestern China and the Tibetan Plateau. There are two important sources of skill for these predictions in western China： interannual variation of SST in the western Pacific and the SST trend in the tropical Pacific. The tropical SST change in the recent two decades, with a warming in the western Pacific and cooling in the eastern Pacific, which is reproduced well by the forecast system, provides a large contribution to the skill of SAT in northwestern China. Additionally, the interannual variation of SST in the western Pacific gives rise to the reliable prediction of SAT around the Tibetan Plateau. It modulates convection around the Maritime Continent and further modulates the variation of SAT on the Tibetan Plateau via the surrounding circulation. This process is evident irrespective of detrending both in observations and the model predictions, and acts as a source of skill in predictions for the Tibetan Plateau. The predictability and reliability demonstrated in this study is potentially useful for climate services providing early warning of extreme climate events and could imply useful economic benefits.