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Yin Tang, Lizhuo Zhang, Dan Huang, Sha Yang and Yingchun Kuang
In view of the current problems of complex models and insufficient data processing in ultra-short-term prediction of photovoltaic power generation, this paper proposes a photovoltaic power ultra-short-term prediction model named HPO-KNN-SRU, based on a S...
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Xiaoyue Yang, Yi Yang, Shenghua Xu, Jiakuan Han, Zhengyuan Chai and Gang Yang
Geographically weighted regression (GWR) is a classical method for estimating nonstationary relationships. Notwithstanding the great potential of the model for processing geographic data, its large-scale application still faces the challenge of high comp...
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Aliya Jangabylova, Alexander Krassovitskiy, Rustam Mussabayev and Irina Ualiyeva
The documents similarity metric is a substantial tool applied in areas such as determining topic in relation to documents, plagiarism detection, or problems necessary to capture the semantic, syntactic, or structural similarity of texts. Evaluated result...
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Marcelo Picolotto Corso, Fabio Luis Perez, Stéfano Frizzo Stefenon, Kin-Choong Yow, Raúl García Ovejero and Valderi Reis Quietinho Leithardt
Contamination on insulators may increase the surface conductivity of the insulator, and as a consequence, electrical discharges occur more frequently, which can lead to interruptions in a power supply. To maintain reliability in an electrical distributio...
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Hendrana Tjahjadi and Kalamullah Ramli
Blood pressure (BP) is an important parameter for the early detection of heart disease because it is associated with symptoms of hypertension or hypotension. A single photoplethysmography (PPG) method for the classification of BP can automatically analyz...
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Antonio Quintero-Rincón, Valeria Muro, Carlos D?Giano, Jorge Prendes and Hadj Batatia
Spike-and-wave discharge (SWD) pattern detection in electroencephalography (EEG) is a crucial signal processing problem in epilepsy applications. It is particularly important for overcoming time-consuming, difficult, and error-prone manual analysis of lo...
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Stanislav A. Eroshenko, Alexandra I. Khalyasmaa, Denis A. Snegirev, Valeria V. Dubailova, Alexey M. Romanov and Denis N. Butusov
The paper reports the forecasting model for multiple time-domain photovoltaic power plants, developed in response to the necessity of bad weather days? accurate and robust power generation forecasting. We provide a brief description of the piloted short-...
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Monika Rani,Dian Prawira,Nurul Mutiah
Pág. 1 - 11
Procurement of the COVID-19 vaccination has led to diverse opinions among Indonesian people on Twitter. Sentiment analysis on Twitter can be carried out to find out public opinion, especially among Twitter users. The data was used in the form of tweets w...
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Supria Supria,Depandi Enda,Muhamad Nasir
Pág. 178 - 184
Sistem kendali robot saat ini telah banyak dibuat dengan menggunakan berbagai metode seperti sensor accelerometer, sensor suara, leap motion. Pada penelitian ini diusulkan pengenalan bentuk tangan secara real time menggunakan leap motion dan K-Nearest Ne...
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Mirko Stojcic, Milorad K. Banjanin, Milan Vasiljevic, Dragana Nedic, Aleksandar Stjepanovic, Dejan Danilovic and Goran Puzic
Delay in data transmission is one of the key performance indicators (KPIs) of a network. The planning and design value of delay in network management is of crucial importance for the optimal allocation of network resources and their performance focuses. ...
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Noor Kamal Al-Qazzaz, Iyden Kamil Mohammed, Halah Kamal Al-Qazzaz, Sawal Hamid Bin Mohd Ali and Siti Anom Ahmad
Countless women and men worldwide have lost their lives to breast cancer (BC). Although researchers from around the world have proposed various diagnostic methods for detecting this disease, there is still room for improvement in the accuracy and efficie...
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Intisar Omar, Muhammad Khan and Andrew Starr
Crack propagation in materials is a complex phenomenon that is influenced by various factors, including dynamic load and temperature. In this study, we investigated the performance of different machine learning models for predicting crack propagation in ...
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Evaristus D. Madyatmadja, Corinthias P. M. Sianipar, Cristofer Wijaya and David J. M. Sembiring
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Aliya Rexit, Mahpirat Muhammat, Xuebin Xu, Wenxiong Kang, Alimjan Aysa and Kurban Ubul
Handwritten signatures have traditionally been used as a common form of recognition and authentication in tasks such as financial transactions and document authentication. However, there are few studies on minority languages such as Uyghur and Kazakh use...
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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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Nicola Altini, Giuseppe De Giosa, Nicola Fragasso, Claudia Coscia, Elena Sibilano, Berardino Prencipe, Sardar Mehboob Hussain, Antonio Brunetti, Domenico Buongiorno, Andrea Guerriero, Ilaria Sabina Tatò, Gioacchino Brunetti, Vito Triggiani and Vitoantonio Bevilacqua
The accurate segmentation and identification of vertebrae presents the foundations for spine analysis including fractures, malfunctions and other visual insights. The large-scale vertebrae segmentation challenge (VerSe), organized as a competition at the...
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Ning Yu and Timothy Haskins
Regional rainfall forecasting is an important issue in hydrology and meteorology. Machine learning algorithms especially deep learning methods have emerged as a part of prediction tools for regional rainfall forecasting. This paper aims to design and imp...
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Maruti Kumar Mudunuru, Nishant Panda, Satish Karra, Gowri Srinivasan, Viet T. Chau, Esteban Rougier, Abigail Hunter and Hari S. Viswanathan
In brittle fracture applications, failure paths, regions where the failure occurs and damage statistics, are some of the key quantities of interest (QoI). High-fidelity models for brittle failure that accurately predict these QoI exist but are highly com...
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Damar Dananjaya,Indah Werdiningsih,Rini Semiati
Pág. 13 - 22
Background: Data on early childhood disease collected in clinics has accumulated into big data. Those data can be used for classification of early childhood diseases to help medical staff in diagnosing diseases that attack early childhoods.Objective: Thi...
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Rozzi Kesuma Dinata
Pada penelitian ini diimplementasikan algoritma K-Nearest Neighbor dalam pengklasifikasian Sekolah Menengah Pertama/Sederajat berdasarkan peminatan calon siswa. Tujuan penelitian ini adalah untuk memudahkan pengguna dalam menemukan sekolah SMP/sederajat ...
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