Lipase 发表于 2025-3-21 20:05:55
书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0241680<br><br> <br><br>书目名称Cutting Edge Applications of Computational Intelligence Tools and Techniques读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0241680<br><br> <br><br>相容 发表于 2025-3-21 21:32:50
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Using Artificial Neural Networks to Predict Critical Displacement and Stress Values in the Proximal d results (displacements and stresses) were organized as input and output data, respectively. The ANN was trained and then its accuracy was verified. It was observed that artificial NN can accurately forecast displacements and stresses while also saving a significant amount of computing time.粗野 发表于 2025-3-22 06:00:36
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Computational Intelligence Methods for User Matchingo fully leverage the interdependence between them. In contrast, our approach integrates spatial-temporal information to enhance user identification accuracy, through a three-step process. First, we use kernel density estimation to measure the similarity of users’ trajectories, taking both spatial an蔓藤图饰 发表于 2025-3-22 14:18:14
ATIAS: A Model for Understanding Intentions to Use AI Technologyrch on human trust in AI systems, which tends to focus on either ethical factors or technology acceptance factors. By combining both types of factors in a hybrid model, the approach aims to provide a more comprehensive understanding of why people use AI systems. ATIAS may prove valuable for policyma蔓藤图饰 发表于 2025-3-22 20:19:36
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Feature Importance Study for Biogas Production from POME Treatment Plants Using Out-of-Bag Permutatid hydrogen sulfide emission. Temperature, pH and organic loading rate were found to be the most influential parameters for methane and carbon dioxide production, while pH was replaced by suspended solids the case of hydrogen sulfide. The final random forest machine learning model generated performaningenue 发表于 2025-3-23 03:48:04
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Towards an Enhanced and Lightweight Face Authentication Systemuirements. To achieve this, we explore two works with different model designs, research focuses, and potential solutions. In the first work, we try to enhance a usual face recognition model with additional task capability without any additional storage cost. Concretely, we first analyze the two task