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Rui Gao, Weiling Guo, Hongxing Wang, Xuewu Li and Zhiguo Xing
KNN piezoelectric ceramics are of great importance in the field of scientific research due to their high Curie temperature, good electrical properties, etc. The application of potassium sodium niobate K0.5Na0.5NbO3 (KNN) is strictly limited due to the vo...
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Tri Agus Setiawan,Romi Satria Wahono,Abdul Syukur
Pág. 76 - 81
Abstract: Algoritma k Nearest Neighbor (kNN) merupakan metode untuk melakukan klasifikasi terhadap objek baru berdasarkan k tetangga terdekatnya. Algoritma kNN memiliki kelebihan karena sederhana, efektif dan telah banyak digunakan pada banyak masalah kl...
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Paulo J. S. Ferreira, João M. P. Cardoso and João Mendes-Moreira
The kNN machine learning method is widely used as a classifier in Human Activity Recognition (HAR) systems. Although the kNN algorithm works similarly both online and in offline mode, the use of all training instances is much more critical online than of...
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(1) Nadzurah Zainal Abidin (Department of Computer Science, International Islamic University Malaysia, Malaysia) (2) Amelia Ritahani Ismail (Department of Computer Science, International Islamic University Malaysia, Malaysia)
Pág. 304 - 317
K-nearest neighbors (KNN) has been extensively used as imputation algorithm to substitute missing data with plausible values. One of the successes of KNN imputation is the ability to measure the missing data simulated from its nearest neighbors robustly....
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Srushti Vichare, Gaurav Nanda and Raji Sundararajan
In this research, we analyzed narratives from the National Electronic Injury Surveillance System (NEISS) dataset to predict the top two injury codes using a comparative study of ensemble machine learning (ML) models. Four ensemble models were evaluated: ...
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Manuel Bullejos, David Cabezas, Manuel Martín-Martín and Francisco Javier Alcalá
The k-nearest neighbors (KNN) algorithm is a non-parametric supervised machine learning classifier; which uses proximity and similarity to make classifications or predictions about the grouping of an individual data point. This ability makes the KNN algo...
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Luong Vuong Nguyen, Quoc-Trinh Vo and Tri-Hai Nguyen
In the current era of e-commerce, users are overwhelmed with countless products, making it difficult to find relevant items. Recommendation systems generate suggestions based on user preferences, to avoid information overload. Collaborative filtering is ...
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Imene Bareche and Ying Xia
The magnitude of highly dynamic spatial data is expanding rapidly due to the instantaneous evolution of mobile technology, resulting in challenges for continuous queries. We propose a novel indexing approach model, namely, the Velocity SpatioTemporal ind...
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Evangelos Rozos, Demetris Koutsoyiannis and Alberto Montanari
Uncertainty is inherent in the modelling of any physical processes. Regarding hydrological modelling, the uncertainty has multiple sources including the measurement errors of the stresses (the model inputs), the measurement errors of the hydrological pro...
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Ming Li, Jun Tian, Yuliang Wang, Haiyang Zhang, Dongping Yang and Meng Lei
Realizing the rapid measurement of coal moisture content (MC) is of great significance. However, existing measurement methods are time-consuming and damage the original properties of the samples. To address these concerns, a coal MC intelligent measureme...
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Diego Lopez-Bernal, David Balderas, Pedro Ponce and Arturo Molina
One of the main focuses of Education 4.0 is to provide students with knowledge on disruptive technologies, such as Machine Learning (ML), as well as the skills to implement this knowledge to solve real-life problems. Therefore, both students and professo...
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Jasmir Jasmir, Siti Nurmaini and Bambang Tutuko
Text classification is an important component in many applications. Text classification has attracted the attention of researchers to continue to develop innovations and build new classification models that are sourced from clinical trial texts. In build...
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Ye Gu, Shuyou Zhang, Lemiao Qiu, Zili Wang and Lichun Zhang
The conversion from functional requirements (FRs) to design parameters is the foundation of product customization. However, original customer needs usually result in incomplete FRs, limited by customers? incomprehension on the design requirements of thes...
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Majid Abdolrazzagh-Nezhad, Shokooh Pour Mahyabadi, Ali Ebrahimpoor
Pág. 1 - 15
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Karshiev Sanjar, Olimov Bekhzod, Jaesoo Kim, Anand Paul and Jeonghong Kim
Accurate house price forecasts are very important for formulating national economic policies. In this paper, we offer an effective method to predict houses? sale prices. Our algorithm includes one-hot encoding to convert text data into numeric data, feat...
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Omar Haji Kombo, Santhi Kumaran, Yahya H. Sheikh, Alastair Bovim and Kayalvizhi Jayavel
Reliable seasonal prediction of groundwater levels is not always possible when the quality and the amount of available on-site groundwater data are limited. In the present work, a hybrid K-Nearest Neighbor-Random Forest (KNN-RF) is used for the predictio...
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Ameer Ali, Mohammed A. T. Alrubei, Laith Falah Mohammed Hassan, Mohannad A. M. Al-Ja'afari, Saif H. Abdulwahed
Pág. 175 - 181
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Ameer Ali, Mohammed A. T. Alrubei, Laith Falah Mohammed Hassan, Mohannad A. M. Al-Ja'afari, Saif H. Abdulwahed
Pág. 175 - 181
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I-Fang Su, Ding-Li Chen, Chiang Lee and Yu-Chi Chung
In many spatial applications, users are only interested in data objects that are visible to them. Hence, finding visible data objects is an important operation in these real-world spatial applications. This study addressed a new type of spatial query, th...
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Shwetha V,Dr.Vijaya laxmi,Dhanin Anoop Asarpota,Himanshu Verma
A sizable population around the world has some form of hearing or speaking disability. This creates a communication barrier among them and the rest of the world. Sign language was introduced to bridge this gap. The objective is to design a glove that can...
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