In this study, the gray wolf algorithm was applied to optimize the water-cooled central chilling system operation in a commercial office building. The optimization objective was to maximize the system ...
ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...
In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...
Amid the wave of the digital age, advanced technologies such as big data, artificial intelligence, and cloud computing are driving precise analysis and forecasting across various fields. This paper ...
Abstract: In this paper, we consider the problem of learning a linear regression model on a data domain of interest (target) given few samples. To aid learning, we are provided with a set of ...
Background: The aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP). Conclusion: This ...
eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
GameSpot may get a commission from retail offers. A number of Call of Duty: Black Ops games over the years have had multiple endings, but Black Ops 6 will not continue this tradition. Associate ...
Abstract: Linear regression is a classical statistical model with a wide range of applications. The function of linear regression is to predict the value of a dependent variable (the output) given an ...
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