# Engineering Applications of Artificial Intelligence

**Type:** Journals  
**Canonical URL:** https://scholariq.org/journals/engineering-applications-of-artificial-intelligence/

## Facts

| Field | Value |
| --- | --- |
| APC (USD) | 3,170 |
| Citations | 320,550 |
| h-index | 184 |
| Homepage | https://www.journals.elsevier.com/engineering-applications-of-artificial-intelligence |
| Open Access | false |
| ISSN-L | 0952-1976 |
| ISSNs | 0952-1976,1873-6769 |
| OpenAlex ID | https://openalex.org/S900972176 |
| Publisher | Elsevier BV |
| Works | 14,374 |

## Journal papers

Showing 12 of 28.

- [Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach : A review of two decades of research](https://scholariq.org/papers/multi-fault-diagnosis-of-industrial-rotating-machines-using-data-driven-approach/)
- [Semantic segmentation using Vision Transformers: A survey](https://scholariq.org/papers/semantic-segmentation-using-vision-transformers-a-survey-2/)
- [A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools](https://scholariq.org/papers/a-systematic-literature-review-on-software-defect-prediction-using-artificial/)
- [Towards a machine learning-based framework for DDOS attack detection in software-defined IoT (SD-IoT) networks](https://scholariq.org/papers/towards-a-machine-learning-based-framework-for-ddos-attack-detection-in-software/)
- [An optimum multi-level image thresholding segmentation using non-local means 2D histogram and exponential Kbest gravitational search algorithm](https://scholariq.org/papers/an-optimum-multi-level-image-thresholding-segmentation-using-non-local-means-2d/)
- [A fuzzy TOPSIS and Rough Set based approach for mechanism analysis of product infant failure](https://scholariq.org/papers/a-fuzzy-topsis-and-rough-set-based-approach-for-mechanism-analysis-of-product/)
- [Fruit and vegetable disease detection and classification: Recent trends, challenges, and future opportunities](https://scholariq.org/papers/fruit-and-vegetable-disease-detection-and-classification-recent-trends/)
- [Forecasting of short-term traffic-flow based on improved neurofuzzy models via emotional temporal difference learning algorithm](https://scholariq.org/papers/forecasting-of-short-term-traffic-flow-based-on-improved-neurofuzzy-models-via/)
- [Assessing and classifying risk of pipeline third-party interference based on fault tree and SOM](https://scholariq.org/papers/assessing-and-classifying-risk-of-pipeline-third-party-interference-based-on/)
- [Short-Term Electricity-Load Forecasting by deep learning: A comprehensive survey](https://scholariq.org/papers/short-term-electricity-load-forecasting-by-deep-learning-a-comprehensive-survey/)
- [A reinforcement learning approach for waterflooding optimization in petroleum reservoirs](https://scholariq.org/papers/a-reinforcement-learning-approach-for-waterflooding-optimization-in-petroleum/)
- [Privacy enabled driver behavior analysis in heterogeneous IoV using federated learning](https://scholariq.org/papers/privacy-enabled-driver-behavior-analysis-in-heterogeneous-iov-using-federated/)

## Journal top topics

Showing 8 of 25.

- [Fault Detection and Control Systems](https://scholariq.org/topics/fault-detection-and-control-systems/)
- [Machine Fault Diagnosis Techniques](https://scholariq.org/topics/machine-fault-diagnosis-techniques/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Neural Networks and Applications](https://scholariq.org/topics/neural-networks-and-applications/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Multi-Criteria Decision Making](https://scholariq.org/topics/multi-criteria-decision-making/)
- [Metaheuristic Optimization Algorithms Research](https://scholariq.org/topics/metaheuristic-optimization-algorithms-research/)
- [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.