实验室前沿研发
上海最优控制与数据智能实验室
SCI Lab（上海最优控制与数据智能实验室）由公司首席算法科学家、上海交通大学王嘉教授创立，聚焦水务场景的智能优化与数据挖掘，核心研究方向包括：水质连续时间序列预测模型、供水管网参数优化与异常检测、微生物生物相智能识别与统计分析等。实验室深度融合深度学习与信息演化理论，推动水务领域的AI技术应用。
核心研究方向
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水质连续时间序列预测模型
基于多源传感器数据（pH值、浊度、COD、重金属等），构建时序动态预测模型，结合物理机理与数据驱动方法，实现水质变化的超前预警与因果推断。
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供水管网参数优化与异常检测
通过水力模型与AI的联合仿真，优化管网压力、流量分配等参数，并检测漏损、爆管等异常事件，降低损耗。
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微生物生物相
利用计算机视觉（CV）与元基因组学分析，识别活性污泥中的微生物群落结构，关联污水处理效能（如脱氮除磷效率）。
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深度融合深度学习与信息演化理论
将信息熵、混沌理论等与深度学习结合，构建水务系统的跨尺度演化模型。
水务应用
AI节水
AI节水系统结合动态水力模型、 DMA分区系统，实现爆管点的精准定位、评估管段的渗漏程度等级，并结合现状工况和运行参数，进行综合调度和压力管理，降低供水管网的漏损率。
AI节药
AI节药系统根据流量、浊度、光学影像等参数变化，通过叠加深度神经网络算法与计算机视觉技术有效感知和预测水处理状态，实现混凝剂、除磷剂、消毒剂等药剂的精准投加。
AI节能
AI节能系统通过寻优搜索算法对水泵进行组合搭配，基于水泵特性模型模拟各种搭配，在边界条件内进行路径搜索，使用AI模型迭代生成最优工作方案。根据不同运行负荷、配电负载找出最优运行组合,实现泵组的最优节能运行。
AI运维
AI设备运维系统通过对机电设备的振动、温度、电气和运行时间等要素进行采集、频谱分析与特征识别，建立设备状态监测与评价。采用工况识别、故障诊断、性能预测等多模态AI算法进行综合分析，识别异常并发出预警。
AI专家
AI专家系统基于行业知识图谱与人工智能大模型搭建，实现知识问答、员工培训、故障诊断与应急处置等任务,并以文字、语音、视频等方式与使用者交互，是水务企业的智能运营助手。
AI防汛
AI防汛系统通过处理实时气象、地形图像、实时水文等数据，计算雨洪频率、水情水势等参量，分析不同风险因素的相互关系，预测洪水的路径和影响区域，评估灾害发生的概率和影响，实现“预报-预警-预演-预案”。
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