# Machine learning approach of detecting anomalies and forecasting time-series of IoT devices

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/machine-learning-approach-of-detecting-anomalies-and-forecasting-time-series-of/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Amer Malki,El‐Sayed Atlam,Ibrahim Gad |
| Citations | 70 |
| DOI | 10.1016/j.aej.2022.02.038 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.sciencedirect.com/science/article/pii/S1110016822001260/pdf |
| OpenAlex ID | https://openalex.org/W4214614245 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Ibrahim Gad](https://scholariq.org/researchers/ibrahim-gad/)

## Paper primary topic

- [Electricity Theft Detection Techniques](https://scholariq.org/topics/electricity-theft-detection-techniques/)

## Paper topics

- [Electricity Theft Detection Techniques](https://scholariq.org/topics/electricity-theft-detection-techniques/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Energy Load and Power Forecasting](https://scholariq.org/topics/energy-load-and-power-forecasting/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.