In　order　to　meet　the　requirements　of　controlling　the　water　quality　of　electric　power,　electronics　and　other　manufacturing　industries　and　reducing　energy　consumption　through　remote　operation　and　maintenance　system,　an　intelligent　remote　operation　and　maintenance　system　of　ultra-pure　water　is　constructed　for　ultra-pure　water　manufacturing　in　electronic　industry.　radial　basis　function　neural　network　and　generalized　regression　neural　network　are　used　to　fit　and　predict　the　effluent　quality　of　ultra-pure　water.　Through　data　analysis,　the　above　algorithm　is　used　to　realize　the　accurate　prediction　of　ultra-pure　water　system　and　intelligent　adaptive　control,　which　improves　the　accuracy　and　convergence　speed　of　the　algorithm.　The　results　show　that　on　the　basis　of　the　simulation　of　the　model,　the　purpose　of　improving　water　production　quality,　saving　energy　and　reducing　consumption　can　be　achieved　through　backwater　utilization　and　frequency　conversion　speed　regulation.　©　Content　from　this　work　may　be　used　under　the　terms　of　the　Creative　Commons　Attribution　3.0　licence.