|
|
|
|
|
Jizhao Wang, Yunyi Liang, Jinjun Tang and Zhizhou Wu
This research contributes to the development of a technological method to obtain highly accurate vehicle trajectory data. The reconstructed trajectory data play a key role in traffic state prediction, traffic management and the decision making of autonom...
ver más
|
|
|
|
|
|
|
|
|
|
|
Carlos Alfonso Zafra-Mejía, Hugo Alexander Rondón-Quintana and Carlos Felipe Urazán-Bonells
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply sy...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Saikat Das, Mohammad Ashrafuzzaman, Frederick T. Sheldon and Sajjan Shiva
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical infrastru...
ver más
|
|
|
|
|
|
|
|
|
|
|
Woo-Hyun Choi and Jung-Ho Lewe
This study proposes a deep learning model utilizing the BACnet (Building Automation and Control Network) protocol for the real-time detection of mechanical faults and security vulnerabilities in building automation systems. Integrating various machine le...
ver más
|
|
|
|
|
|
|
|
|
|
|
Liqiu Chen, Chongshi Gu, Sen Zheng and Yanbo Wang
Real and effective monitoring data are crucial in assessing the structural safety of dams. Gross errors, resulting from manual mismeasurement, instrument failure, or other factors, can significantly impact the evaluation process. It is imperative to elim...
ver más
|
|
|
|
|
|
|
|
|
|
|
Károly Héberger
Background: The development and application of machine learning (ML) methods have become so fast that almost nobody can follow their developments in every detail. It is no wonder that numerous errors and inconsistencies in their usage have also spread wi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fan Lin, Dengjie Chen, Cheng Liu and Jincheng He
This study pioneered a non-destructive testing approach to evaluating the physicochemical properties of golden passion fruit by developing a platform to analyze the fruit?s electrical characteristics. By using dielectric properties, the method accurately...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chunhyun Paik, Yongjoo Chung and Young Jin Kim
The estimation of power curve is the central task for efficient operation and prediction of wind power generation. It is often the case, however, that the actual data exhibit a great deal of variations in power output with respect to wind speed, and thus...
ver más
|
|
|
|
|
|
|
|
|
|
|
Francisco Melo Pereira and Rute C. Sofia
This paper provides an analysis of two machine learning algorithms, density-based spatial clustering of applications with noise (DBSCAN) and the local outlier factor (LOF), applied in the detection of outliers in the context of a continuous framework for...
ver más
|
|
|
|
|
|