With the growing advances in technology and transformation to digital services, the world is becoming more connected and more complex. Huge heterogeneous data are generated at rapid speed from various types of sensors. Augmented with artificial intelligence and machine learning and internet of things, latent relations, and new insights can be captured helping in optimizing plans and resource utilization, improving infrastructure, and enhancing quality of services.A “spatial data management system” is a way to take care of data that has something to do with space. This could include data such as maps, satellite images, and GPS data. A temporal data management system is a system designed to manage data that has a temporal component. This could include data such as weather data, financial data, and social media data. Some advanced techniques used in spatial and temporal data management systems include geospatial indexing for efficient querying and retrieval of location-based data, time-series analysis for understanding and predicting temporal patterns in datasets like weather or financial trends, machine learning algorithms for uncovering hidden patterns and correlations in large and complex datasets, and integration with Internet of Things (IoT) technologies for real-time data collection and analysis. These techniques, augmented with artificial intelligence, enable the extraction of latent relations and insights, thereby optimizing plans, improving infrastructure, and enhancing the quality of services. This book provides essential technical knowledge, best practices, and case studies on the state-of-the-art techniques of artificial intelligence and machine learning for spatiotemporal data analysis and modeling. The book is composed of several chapters written by experts in their fields and focusing on several applications including recommendation systems, big data analytics, supply chains and e-commerce, energy consumption and demand forecasting, and traffic and environmental monitoring. It can be used as academic reference at graduate level or by professionals in science and engineering related fields such as data science and engineering, big data analytics and mining, artificial intelligence, machine learning and deep learning, cloud computing, and internet of things.

• 关于产品：
• ● 正版保障：本网站隶属于中国国际图书贸易集团公司，确保所有图书都是100%正版。
• ● 环保纸张：进口图书大多使用的都是环保轻型张，颜色偏黄，重量比较轻。
• ● 毛边版：即书翻页的地方，故意做成了参差不齐的样子，一般为精装版，更具收藏价值。
• 
  关于退换货：
• 由于预订产品的特殊性，采购订单正式发订后，买方不得无故取消全部或部分产品的订购。
• 由于进口图书的特殊性，发生以下情况的，请直接拒收货物，由快递返回：
• ● 外包装破损/发错货/少发货/图书外观破损/图书配件不全（例如：光盘等）
  并请在工作日通过电话400-008-1110联系我们。
• 签收后，如发生以下情况，请在签收后的5个工作日内联系客服办理退换货：
• ● 缺页/错页/错印/脱线
• 
  关于发货时间：
• 一般情况下：
• ●【现货】 下单后48小时内由北京（库房）发出快递。
• ●【预订】【预售】下单后国外发货，到货时间预计5-8周左右，店铺默认中通快递，如需顺丰快递邮费到付。
• ● 需要开具发票的客户，发货时间可能在上述基础上再延后1-2个工作日（紧急发票需求，请联系010-68433105/3213）；
• ● 如遇其他特殊原因，对发货时间有影响的，我们会第一时间在网站公告，敬请留意。
• 
  关于到货时间：
• 由于进口图书入境入库后，都是委托第三方快递发货，所以我们只能保证在规定时间内发出，但无法为您保证确切的到货时间。
• ● 主要城市一般2-4天
• ● 偏远地区一般4-7天
• 
  关于接听咨询电话的时间：
• 010-68433105/3213正常接听咨询电话的时间为：周一至周五上午8：30～下午5：00，周六、日及法定节假日休息，将无法接听来电，敬请谅解。
• 其它时间您也可以通过邮件联系我们：customer@readgo.cn,工作日会优先处理。
• 
  关于快递：
• ● 已付款订单：主要由中通、宅急送负责派送，订单进度查询请拨打010-68433105/3213。