使用 DateTime 作为时间特征对时间序列模型进行评分时出错“执行服务 XXXX 消息时出错::无法处理请求:[对于输入字符串:”

• 针对使用DateTime数据类型作为 TEMPORAL 特征的时间序列模型对新数据进行评分时收到以下错误

WARN  c.t.a.a.r.SyncPredictiveScoringResource - Failed to score with:PredictiveScoringRequest [dataSource=DatasetRef [dataRef=CsvBodyDataRef [hasHeader=true, uri=body:///, format=csv, data=[data] ], schemaRef=null, filter=, exclusions=[]], modelUri=results:/models/XXXX, scoringName=ignored, importantFieldCount=0, goalName=null, description=null, causalTechnique=FULL_RANGE, preferredCategoricalValues=null, categoricalLimit=null, tags=null, identifierFields=null]
java.lang.NumberFormatException: For input string: "2016-03-08T02:00:00.000Z"
	at java.base/java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
	at java.base/java.lang.Long.parseLong(Long.java:692)
	at java.base/java.lang.Long.valueOf(Long.java:1144)
	at com.thingworx.analytics.unicron.timeseries.TimeSeriesTransformer$Builder.lambda$createRowToKeyedRowFunction$50e661ed$1(TimeSeriesTransformer.java:456)
	at com.thingworx.analytics.unicron.timeseries.TimeSeriesTransformer$Builder.lambda$createRowToKeyedRowFunction$114dfc31$1(TimeSeriesTransformer.java:459)
...

• 使用 RealtimeScore 服务进行评分：

let dsref = Resources["InfoTableFunctions"].CreateInfoTableFromDataShape({
    dataShapeName: "AnalyticsDatasetRef"
});


let newEntry = {
   // datasetUri: "body:/", // STRING
    format: undefined, // STRING
    filter: undefined, // STRING
    exclusions: undefined, // INFOTABLE {"dataShape":"GenericStringList"}
    data: me.scoreData // INFOTABLE

};
dsref.AddRow(newEntry);

var predictiveScores = Things["AnalyticsServer_PredictionThing"].RealtimeScore({
	modelUri: "results:/models/" + me.modelID,
    datasetRef: dsref
});