Artificial intelligence has become the loudest conversation in logistics, but at Uber Freight, the technology has been part of the company’s DNA from the beginning. Speaking with Supply Chain ...
The U.S. logistics industry has no shortage of software promising full automation of time-consuming tasks, dashboards, and efficiency gains. Yet for many companies, the real bottleneck comes in ...
Abstract: —The objective is to more accurately forecast phishing attacks that harvest sensitive data from unsuspecting users by utilizing Logistic Regression in comparison to the Novel Random Forest ...
When the maritime trade union Nautilus International asked memberswhat they thought of AI at a forum in January, there was some positive sentiment: “We shouldn’t automatically assume there will be ...
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Issues are used to track todos, bugs, feature requests, and more.
In Table 3, the VIF values for each variable are < 5, which has been reduced as multicollinearity between variables. 3.3. Use the Entropy Weight Method to Weight the Data When exploring the factors ...
Abstract: Logistic regression is a widely utilized machine learning algorithm for binary classification tasks. In this study, the logistic regression algorithm is used to classify whether a disorder ...
With rapid globalization and technological advancements manifesting at rising rates, the complexity of logistics networks has increased exponentially. This is most evident in the military sector where ...
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