Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|
failure prediction | 0.34 | 0.7 | 3084 | 9 | 18 |
failure | 1.83 | 0.4 | 6679 | 34 | 7 |
prediction | 1.01 | 0.6 | 2141 | 58 | 10 |
Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|
failure prediction | 1.14 | 0.9 | 3282 | 95 |
failure prediction threshold exceeded | 1.36 | 0.5 | 868 | 98 |
failure prediction using machine learning | 1.18 | 0.4 | 4508 | 73 |
failure prediction models | 1.15 | 0.7 | 7477 | 18 |
failure prediction apm | 0.16 | 0.2 | 9395 | 70 |
failure prediction dataset | 1.78 | 0.9 | 1620 | 54 |
failure prediction analysis | 1.61 | 0.2 | 9705 | 88 |
failure prediction for autonomous driving | 1.02 | 0.2 | 817 | 95 |
failure prediction models for gas pipeline | 1.93 | 0.3 | 8228 | 90 |
failure prediction of elevator component | 0.59 | 0.8 | 3460 | 38 |
failure prediction of composite materials | 0.28 | 1 | 2418 | 89 |
heart failure prediction | 1.67 | 0.8 | 8535 | 17 |
corporate failure prediction models | 0.57 | 0.1 | 3300 | 48 |
machine failure prediction | 0.61 | 1 | 7665 | 23 |
heart failure prediction dataset | 0.98 | 0.1 | 5213 | 69 |
machine failure prediction using python | 0.17 | 0.5 | 9098 | 8 |
heart failure prediction research paper | 1.11 | 0.4 | 6168 | 71 |
heart failure prediction project report | 0.87 | 0.4 | 6661 | 69 |
machine failure prediction dataset | 1.64 | 0.5 | 3117 | 38 |