预测 - 水库运行管理系统

本接口对新观测数据进行异常识别，计算基于M估计的MZ准则阈值，在阈值范围之外的为异常数据。

请求参数

Body 参数application/json

predict_independent_variables

array [array]

必需

新观测数据的自变量合集，自变量个数要和训练时的自变量数量一致

>= 1 items

number

可选

predict_dependent_variable

array[number]

必需

新观测数据的因变量列表，自变量对应的应变量的值，只能有一个因变量

>= 1 items<= 1 items

model

object

训练得到的模型结果

必需

resid

string

模型残差

必需

fittedvalues

string

模型拟合数据

必需

weights

string

权重

必需

independent_variables

string

必需

训练模型的原始自变量数据

params

string

模型参数

必需

示例

{
    "predict_independent_variables": [
        [
            14.8,
            219.04000000000002,
            3241.7920000000004,
            14.371428571428568,
            21.1,
            22.3,
            20.8,
            0.9946708199115211,
            0.10310169744743485,
            0.06,
            -2.8134107167600364
        ],
        [
            14.0,
            196.0,
            2744.0,
            14.442857142857145,
            20.9,
            25.0,
            22.7,
            -0.23449138957040985,
            0.9721181966290613,
            1.05,
            0.04879016416943204
        ]
    ],
    "predict_dependent_variable": [
        21.7,
        59.1
    ],
    "model": {
        "independent_variables": [
            [
                14.5,
                210.25,
                3048.625,
                8.185714285714285,
                22.8,
                22.8,
                22.8,
                0.9994074007397048,
                0.03442161162274574,
                0.02,
                -3.912023005428146
            ],
            [
                14.3,
                204.49,
                2924.2070000000003,
                10.299999999999999,
                22.8,
                22.8,
                22.8,
                0.998666816288476,
                0.051619667223253764,
                0.03,
                -3.506557897319982
            ],
            [
                14.2,
                201.64,
                2863.2879999999996,
                12.314285714285713,
                20.8,
                22.8,
                22.8,
                0.9976303053065857,
                0.06880242680231986,
                0.04,
                -3.2188758248682006
            ],
            [
                14.3,
                204.49,
                2924.2070000000003,
                14.399999999999997,
                22.3,
                20.8,
                22.8,
                0.9962981749346078,
                0.08596479873744647,
                0.05,
                -2.995732273553991
            ],
            [
                14.8,
                219.04000000000002,
                3241.7920000000004,
                14.371428571428568,
                21.1,
                22.3,
                20.8,
                0.9946708199115211,
                0.10310169744743485,
                0.06,
                -2.8134107167600364
            ],
            [
                14.1,
                198.81,
                2803.221,
                14.428571428571429,
                22.8,
                21.1,
                22.3,
                0.9927487224577402,
                0.1202080448993527,
                0.07,
                -2.659260036932778
            ],
            [
                14.6,
                213.16,
                3112.136,
                14.500000000000002,
                24.6,
                22.8,
                21.1,
                0.9905324521322229,
                0.13727877211326478,
                0.08,
                -2.5257286443082556
            ],
            [
                14.3,
                204.49,
                2924.2070000000003,
                14.571428571428571,
                21.4,
                24.6,
                22.8,
                0.9880226656636976,
                0.15430882066428117,
                0.09,
                -2.4079456086518722
            ],
            [
                14.7,
                216.08999999999997,
                3176.5229999999997,
                14.457142857142857,
                24.2,
                21.4,
                24.6,
                0.9852201067560606,
                0.1712931441814776,
                0.1,
                -2.3025850929940455
            ],
            [
                14.7,
                216.08999999999997,
                3176.5229999999997,
                14.571428571428571,
                23.7,
                24.2,
                21.4,
                0.9821256058680006,
                0.1882267098432442,
                0.11,
                -2.2072749131897207
            ],
            [
                14.8,
                219.04000000000002,
                3241.7920000000004,
                14.514285714285716,
                23.9,
                23.7,
                24.2,
                0.9787400799669153,
                0.2051044998686192,
                0.12,
                -2.120263536200091
            ],
            [
                14.0,
                196.0,
                2744.0,
                14.514285714285716,
                22.7,
                23.9,
                23.7,
                0.9750645322571948,
                0.2219215130041655,

示例代码

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

curl --location --request POST 'http://192.168.11.46:13000/v1/abnormal_recognize/two_step/abnormal_detector' \
--header 'Content-Type: application/json' \
--data-raw '{
    "predict_independent_variables": [
        [
            14.8,
            219.04000000000002,
            3241.7920000000004,
            14.371428571428568,
            21.1,
            22.3,
            20.8,
            0.9946708199115211,
            0.10310169744743485,
            0.06,
            -2.8134107167600364
        ],
        [
            14.0,
            196.0,
            2744.0,
            14.442857142857145,
            20.9,
            25.0,
            22.7,
            -0.23449138957040985,
            0.9721181966290613,
            1.05,
            0.04879016416943204
        ]
    ],
    "predict_dependent_variable": [
        21.7,
        59.1
    ],
    "model": {
        "independent_variables": [
            [
                14.5,
                210.25,
                3048.625,
                8.185714285714285,
                22.8,
                22.8,
                22.8,
                0.9994074007397048,
                0.03442161162274574,
                0.02,
                -3.912023005428146
            ],
            [
                14.3,
                204.49,
                2924.2070000000003,
                10.299999999999999,
                22.8,
                22.8,
                22.8,
                0.998666816288476,
                0.051619667223253764,
                0.03,
                -3.506557897319982
            ],
            [
                14.2,
                201.64,
                2863.2879999999996,
                12.314285714285713,
                20.8,
                22.8,
                22.8,
                0.9976303053065857,
                0.06880242680231986,
                0.04,
                -3.2188758248682006
            ],
            [
                14.3,
                204.49,
                2924.2070000000003,
                14.399999999999997,
                22.3,
                20.8,
                22.8,
                0.9962981749346078,
                0.08596479873744647,
                0.05,
                -2.995732273553991
            ],
            [
                14.8,
                219.04000000000002,
                3241.7920000000004,
                14.371428571428568,
                21.1,
                22.3,
                20.8,
                0.9946708199115211,
                0.10310169744743485,
                0.06,
                -2.8134107167600364
            ],
            [
                14.1,
                198.81,
                2803.221,
                14.428571428571429,
                22.8,
                21.1,
                22.3,
                0.9927487224577402,
                0.1202080448993527,
                0.07,
                -2.659260036932778
            ],
            [
                14.6,
                213.16,
                3112.136,
                14.500000000000002,
                24.6,
                22.8,
                21.1,
                0.9905324521322229,
                0.13727877211326478,
                0.08,
                -2.5257286443082556
            ],
            [
                14.3,
                204.49,
                2924.2070000000003,
                14.571428571428571,
                21.4,
                24.6,
                22.8,
                0.9880226656636976,
                0.15430882066428117,
                0.09,
                -2.4079456086518722
            ],
            [
                14.7,
                216.08999999999997,
                3176.5229999999997,
                14.457142857142857,
                24.2,
                21.4,
                24.6,
                0.9852201067560606,
                0.1712931441814776,
                0.1,
                -2.3025850929940455
            ],
            [
                14.7,
                216.08999999999997,
                3176.5229999999997,
                14.571428571428571,
                23.7,
                24.2,
                21.4,
                0.9821256058680006,
                0.1882267098432442,
                0.11,
                -2.2072749131897207
            ],
            [
                14.8,
                219.04000000000002,
                3241.7920000000004,
                14.514285714285716,
                23.9,
                23.7,
                24.2,
                0.9787400799669153,
                0.2051044998686192,
                0.12,
                -2.120263536200091
            ],
            [
                14.0,
                196.0,
                2744.0,
                14.5142857

返回响应

🟢200成功

application/json

Body

code

integer

响应状态码

必需

msg

string

响应消息

必需

data

object

必需

predict_independent_variables

array[integer]

异常值位置索引

必需

predict_residuals

array[number]

必需

需要检测的数据的残差集合，为一维数组，按照传入的自变量数据的顺序排列

median_zero_thresholds

array [array]

必需

MZ阈值的上下界集合，每条数据的MZ阈值不同，为二维数组。数组中的每条数据，第一个元素为下界阈值，第二个元素为上届阈值

pauta

array[number]

必需

基于残差三倍α的上下界列表, 是基于模型残差计算的固定值，为一维数组，若不需要和mz绘图比较，则可以忽略

示例

{
    "code": 200,
    "msg": "请求成功",
    "data": {
        "abnormal_index_list": [
            1
        ],
        "predict_residuals": [
            -0.23133695569849877,
            37.1686630443015
        ],
        "median_zero_thresholds": [
            [
                -10.850553558751377,
                10.850553558751377
            ],
            [
                -10.849559996212022,
                10.849559996212022
            ]
        ],
        "pauta": [
            -32.58484230742117,
            44.49159275941891
        ]
    }
}