Jie Li^1,3,*, Rongwen Wang², Yongtao Hu^1,3, Jinjun Li¹

Structural Durability & Health Monitoring, Vol.18, No.1, pp. 73-90, 2024, DOI:10.32604/sdhm.2023.044023 - 11 January 2024

Abstract The aging prediction of railway catenary is of profound significance for ensuring the regular operation of electrified trains. However, in real-world scenarios, accurate predictions are challenging due to various interferences. This paper addresses this challenge by proposing a novel method for predicting the aging of railway catenary based on an improved Kalman filter (KF). The proposed method focuses on modifying the priori state estimate covariance and measurement error covariance of the KF to enhance accuracy in complex environments. By comparing the optimal displacement value with the theoretically calculated value based on the thermal expansion effect… More > Graphic Abstract

S. Sakthivel¹, V. Vivekanandhan^2,*, M. Manikandan²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 853-866, 2023, DOI:10.32604/iasc.2023.026289 - 06 June 2022

Abstract Irrigation plays a significant role in various agricultural cropping methods deployed in semiarid and arid regions where valuable water applications and managing are considered crucial concerns. Multiple factors such as weather, soil, water, and crop data need to be considered for irrigation maintenance in an efficient besides uniform manner from multifaceted and different information-based systems. A Multi-Agent System (MAS) has been proposed recently based on diverse agent subsystems with definite objectives for attaining global MAS objective and is deployed on Cloud Computing paradigm capable of gathering information from Wireless Sensor Networks (WSNs) positioned in rice,… More >

V. Ravindra Krishna Chandar^1,*, M. Thangamani²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 165-181, 2022, DOI:10.32604/iasc.2022.022339 - 15 April 2022

Abstract

During patient monitoring, false alert in the Intensive Care Unit (ICU) becomes a major problem. In the category of alarms, pseudo alarms are regarded as having no clinical or therapeutic significance, and thus they result in fatigue alarms. Artifacts are misrepresentations of tissue structures produced by imaging techniques. These Artifacts can invalidate the Arterial Blood Pressure (ABP) signal. Therefore, it is very important to develop algorithms that can detect artifacts. However, ABP has algorithmic shortcomings and limitations of design. This study is aimed at developing a real-time enhancement of independent component analysis (EICA) and time-domain

… More >

Xiaona Zhang^1,*, Jie Feng², Zhen Hong³, Xiaona Rui⁴

Computer Systems Science and Engineering, Vol.42, No.2, pp. 677-688, 2022, DOI:10.32604/csse.2022.023136 - 04 January 2022

Abstract In regards to soil macropores, the solute loss carried by overland flow is a very complex process. In this study, a fuzzy neural network (FNN) model was used to analyze the solute loss on slopes, taking into account the soil macropores. An artificial rainfall simulation experiment was conducted in indoor experimental tanks, and the verification of the model was based on the results. The characteristic scale of the macropores, the rainfall intensity and duration, the slope and the adsorption coefficient of ions, were chosen as the input variables to the Sugeno FNN model. The cumulative More >

Ala’ A. Eshmawi¹, Hesham Alhumyani², Sayed Abdel Khalek³, Rashid A. Saeed², Mahmoud Ragab⁴, Romany F. Mansour^5,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2543-2557, 2022, DOI:10.32604/cmc.2022.021833 - 07 December 2021

Abstract Sentiment analysis or Opinion Mining (OM) has gained significant interest among research communities and entrepreneurs in the recent years. Likewise, Machine Learning (ML) approaches is one of the interesting research domains that are highly helpful and are increasingly applied in several business domains. In this background, the current research paper focuses on the design of automated opinion mining model using Deer Hunting Optimization Algorithm (DHOA) with Fuzzy Neural Network (FNN) abbreviated as DHOA-FNN model. The proposed DHOA-FNN technique involves four different stages namely, preprocessing, feature extraction, classification, and parameter tuning. In addition to the above, More >

Shuangying Liu¹, Weidong Zhang^2,*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 569-575, 2020, DOI:10.32604/iasc.2020.013935

Abstract The constant development of computer technology has greatly facilitated our life. In the past, the agricultural products trade and agricultural products business model were an offline development, through face-to-face transactions. However, with the continuous application of Internet technology, we also have a new exploration on the e-commerce path of agricultural products. The fuzzy neural network algorithm was used to study the electronic commerce path of agricultural products and helped us to carry out the exploration computation of the electronic commerce path of agricultural products. And good calculation results have been obtained. Through our testing of More >

Chung Wen Hung, Wei Lung Mao, Han Yi Huang

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 329-341, 2019, DOI:10.31209/2019.100000093

Abstract Nonlinear system modeling and identification is the one of the most important areas in engineering problem. The paper presents the recurrent fuzzy neural network (RFNN) trained by modified particle swarm optimization (MPSO) methods for identifying the dynamic systems and chaotic observation prediction. The proposed MPSO algorithms mainly modify the calculation formulas of inertia weights. Two MPSOs, namely linear decreasing particle swarm optimization (LDPSO) and adaptive particle swarm optimization (APSO) are developed to enhance the convergence behavior in learning process. The RFNN uses MPSO based method to tune the parameters of the membership functions, and it More >

Shengbiao Wu^1,2,3, Weihua Cao^1,3,*, Can Liu^1,3, Min Wu^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.116, No.3, pp. 433-453, 2018, DOI:10.31614/cmes.2018.03309

Abstract A computer-aided tuning method that combines T-S fuzzy neural network (T-S FNN) and offers improved space mapping (SM) is presented in this study. This method consists of three main aspects. First, the coupling matrix is effectively extracted under the influence of phase shift and cavity loss after the initial tuning. Second, the surrogate model is realized by using a T-S FNN based on subspace clustering. Third, the mapping relationship between the actual and the surrogate models is established by the improved space mapping algorithm, and the optimal position of the tuning screws are found by More >