|
|
|
|
|
Waleed Albattah and Saleh Albahli
Handwritten character recognition is a computer-vision-system problem that is still critical and challenging in many computer-vision tasks. With the increased interest in handwriting recognition as well as the developments in machine-learning and deep-le...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mun Fie Tsoi
Pág. pp. 48 - 52
|
|
|
|
|
|
|
|
|
|
|
Vaia I. Kontopoulou, Athanasios D. Panagopoulos, Ioannis Kakkos and George K. Matsopoulos
In the broad scientific field of time series forecasting, the ARIMA models and their variants have been widely applied for half a century now due to their mathematical simplicity and flexibility in application. However, with the recent advances in the de...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jianjun Ni, Yan Chen, Yu Gu, Xiaolong Fang and Pengfei Shi
|
|
|
|
|
|
|
|
|
|
|
Claudio Maino, Antonio Mastropietro, Luca Sorrentino, Enrico Busto, Daniela Misul and Ezio Spessa
Hybrid electric vehicles are, nowadays, considered as one of the most promising technologies for reducing on-road greenhouse gases and pollutant emissions. Such a goal can be accomplished by developing an intelligent energy management system which could ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kudakwashe Zvarevashe and Oludayo Olugbara
Automatic recognition of emotion is important for facilitating seamless interactivity between a human being and intelligent robot towards the full realization of a smart society. The methods of signal processing and machine learning are widely applied to...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yue Hu, Weimin Li, Kun Xu, Taimoor Zahid, Feiyan Qin and Chenming Li
An energy management strategy (EMS) is important for hybrid electric vehicles (HEVs) since it plays a decisive role on the performance of the vehicle. However, the variation of future driving conditions deeply influences the effectiveness of the EMS. Mos...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chan-Uk Yeom and Keun-Chang Kwak
This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM) with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK)-based ELM to develop a sy...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yue Hu, Weimin Li, Hui Xu and Guoqing Xu
In order to realize the online learning of a hybrid electric vehicle (HEV) control strategy, a fuzzy Q-learning (FQL) method is proposed in this paper. FQL control strategies consists of two parts: The optimal action-value function Q*(x,u) estimator netw...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rudi Haryadi,Ade Gafar Abdullah10.17509/invotec.v11i2.2148 Abstract views: 383 PDF downloads: 252
Learning of vocational school learning should be able to prepare students who have qualified skills to fit the demands of the realistic activity of industry. Professional activities within the workplace should be integrated completed the learning process...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mun Fie Tsoi
Pág. pp. 48 - 52
|
|
|
|
|
|
|
|
|
|
|
Wenxia You, Daopeng Guo, Yonghua Wu and Wenwu Li
Accurate multivariate load forecasting plays an important role in the planning management and safe operation of integrated energy systems. In order to simultaneously reduce the prediction bias and variance, a hybrid ensemble learning method for load fore...
ver más
|
|
|
|
|
|
|
|
|
|
|
A. M. Mutawa
Background: COVID-19 genetic sequence research is crucial despite immunizations and pandemic control. COVID-19-causing SARS-CoV-2 must be understood genomically for several reasons. New viral strains may resist vaccines. Categorizing genetic sequences he...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ananthi Claral Mary.T
Pág. pp. 46 - 61
|
|
|
|
|
|
|
|
|
|
|
Rubén San-Segundo, Lucía Angulo, Manuel Gil-Martín, David Carramiñana and Ana M. Bernardos
Objective: This paper describes the development of hybrid artificial intelligence strategies for drone navigation. Methods: The navigation module combines a deep learning model with a rule-based engine depending on the agent state. The deep learning mode...
ver más
|
|
|
|
|
|
|
|
|
|
|
Gilbert Hinge, Mohamed A. Hamouda and Mohamed M. Mohamed
In recent years, there has been a growing interest in flood susceptibility modeling. In this study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the nature and evolution of literature, intellectual structure networks, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lei Li, Xiaobao Zeng, Xinpeng Pan, Ling Peng, Yuyang Tan and Jianxin Liu
Microseismic monitoring plays an essential role for reservoir characterization and earthquake disaster monitoring and early warning. The accuracy of the subsurface velocity model directly affects the precision of event localization and subsequent process...
ver más
|
|
|
|
|
|
|
|
|
|
|
Waseem Abbas, Zuping Zhang, Muhammad Asim, Junhong Chen and Sadique Ahmad
In the ever-expanding online fashion market, businesses in the clothing sales sector are presented with substantial growth opportunities. To utilize this potential, it is crucial to implement effective methods for accurately identifying clothing items. T...
ver más
|
|
|
|
|
|
|
|
|
|
|
Adel Hassan A. Gadhi, Shelton Peiris and David E. Allen
This paper examines the predictive ability of volatility in time series and investigates the effect of tradition learning methods blending with the Wasserstein generative adversarial network with gradient penalty (WGAN-GP). Using Brent crude oil returns ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Soo Boon Ng, Wang Siyu, Li Min, Joshua Chin
Pág. 131 - 137
|
|
|
|
|
|