Their findings are detailed in the study “Efficient Energy Consumption: Leveraging AI Models for Appliance Detection,” published in the Journal of Low Power Electronics and Applications, where the ...

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...

ABSTRACT: The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ...

Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest neighbor (ANN) ...

Nearest neighbour classification techniques, particularly the k‐nearest neighbour (kNN) algorithm, have long been valued for their simplicity and effectiveness in pattern recognition and data ...

This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...

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Abstract: In education, for topics delivery still has abstract characteristic. That abstract means the topic cannot be explained in picture and text only. One of the topics is human body's system.

Abstract: K-nearest neighbor (KNN) is a common classification method for data mining techniques. It has been widely used in many fields because of the implementation ...