Table 1 Literature comparison.
From: Artificial intelligence CNN for information system optimization and decision support model
Literature | Research task | Computing technique | Advantage | Limitation |
|---|---|---|---|---|
Waqar26 | Architectural engineering | AI/ML | Risk analysis | Single field, limited integration |
Settembre-Blundo27 | Enterprise operation | Information model | Multidimensional risk assessment | Insufficient dynamic adaptability |
Ehtisham28 | Wood structure damage | CNN + image processing | Feature extraction | Single task, low universality |
Narmadha & Vijayakumar29 | Traffic flow forecast | CNN + LSTM | Time series prediction | Single scene, poor robustness |
Nizam30 | IoT anomaly detection | Depth anomaly detection | Real time identification | Cloud workflow has limited generality. |
Chandrasiri & Meedeniya33 | Cloud workflow scheduling | Deep learning | Energy efficiency optimization | Single goal, lack of closed loop |
Aditi34 | Cloud resource allocation | CNN | Resource bottleneck analysis | Single scene, insufficient adaptability of dynamic load |
Simaiya35 | Cloud load balancing | Hybrid deep learning + optimization | Load balancing | Single objective optimization, lack of end-to-end integration |
