Ana Elena de Villalobos^1,2,*, María Andrea Long^1,2

Phyton-International Journal of Experimental Botany, Vol.93, No.8, pp. 2037-2050, 2024, DOI:10.32604/phyton.2024.053928

Abstract Livestock grazing has a significant impact on natural grasslands, with approximately one-third of the world’s land area dedicated to this industry. Around 20% of global grasslands are highly degraded due to overgrazing, affecting their productivity and conservation capacity. Best practices are required to ensure sustainable livestock production that supports biodiversity. The Intermediate Disturbance Hypothesis (IDH) suggests that environments with moderate levels of disturbance exhibit a higher species diversity. Moderate grazing can reduce the dominance of certain species, thereby enhancing plant diversity. However, concerns arise regarding the increase of exotic and unpalatable species under moderate grazing… More >

Liang Zeng^1,2, Mai Hu¹, Chenning Zhang¹, Quan Yuan¹, Shanshan Wang^1,2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1677-1709, 2024, DOI:10.32604/cmc.2024.049717

Abstract Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines. To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization (NGO) algorithm, particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes, this study introduces an advanced Improved Northern Goshawk Optimization (INGO) algorithm. This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency. Initially, a tent chaotic map is employed in the initialization phase to generate a diverse initial population, providing high-quality feasible solutions. Subsequently, after… More >

Zeyi Wang¹, Mingxi Jiao¹, Daliang Wang¹, Minxu Liu¹, Minglei Jiang², He Wang³, Shiqiang Li^3,*

Energy Engineering, Vol.121, No.8, pp. 2275-2291, 2024, DOI:10.32604/ee.2024.028223

Abstract This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight method. Three different electrical quantities are selected as observations in the compressed sensing algorithm. The entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance levels. Subsequently, by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,… More >

Feng Zhao, Guangdi Liu^*, Xiaoqiang Chen, Ying Wang

Energy Engineering, Vol.121, No.7, pp. 1865-1882, 2024, DOI:10.32604/ee.2024.048209

Abstract In light of the prevailing issue that the existing convolutional neural network (CNN) power quality disturbance identification method can only extract single-scale features, which leads to a lack of feature information and weak anti-noise performance, a new approach for identifying power quality disturbances based on an adaptive Kalman filter (KF) and multi-scale channel attention (MS-CAM) fused convolutional neural network is suggested. Single and composite-disruption signals are generated through simulation. The adaptive maximum likelihood Kalman filter is employed for noise reduction in the initial disturbance signal, and subsequent integration of multi-scale features into the conventional CNN… More >

Xiaofeng Yang^1,3,4, Wei Wang^1,3,4,*, Yujie Shen^2,4, Changning Liu^1,3,4, Tianyi Zhang^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1485-1506, 2024, DOI:10.32604/cmes.2024.049837

Abstract This paper addresses the impact of vertical vibration negative effects, unbalanced radial forces generated by the static eccentricity of the hub motor, and road excitation on the suspension performance of Hub Motor Driven Vehicle (HMDV). A dynamic inertial suspension based on Active Disturbance Rejection Control (ADRC) is proposed, combining the vertical dynamic characteristics of dynamic inertial suspension with the features of ADRC, which distinguishes between internal and external disturbances and arranges the transition process. Firstly, a simulation model of the static eccentricity of the hub motor is established to simulate the unbalanced radial electromagnetic force… More > Graphic Abstract

Lianghao Hua^1,2, Jianfeng Zhang^1,*, Dejie Li³, Xiaobo Xi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2129-2157, 2024, DOI:10.32604/cmes.2023.030535

Abstract With the increasing prevalence of high-order systems in engineering applications, these systems often exhibit significant disturbances and can be challenging to model accurately. As a result, the active disturbance rejection controller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmanned aerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances and the possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address these issues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neural network (RBFNN) with a More > Graphic Abstract

Eun Kyoung Han, Hae Kyoung Son^*

International Journal of Mental Health Promotion, Vol.25, No.11, pp. 1197-1208, 2023, DOI:10.32604/ijmhp.2023.041560

Abstract Dementia prevalence has soared due to population aging. In Mild Cognitive Impairment (MCI) as a pre-dementia stage, sleep disturbances have raised much interest as a factor in a bidirectional relationship with cognitive decline. Thus, this study developed the Sleep and Cognition Enhancement Multimodal Intervention (SCEMI) based on Lazarus’ multimodal approach and conducted a randomized controlled experiment to investigate the effects of the novel program on sleep and cognition in MCI elderly. The participants were 55 MCI elderly with sleep disturbances at two dementia care centers located in S-city, Gyeonggi-do, South Korea (n = 25 in… More >

Yanjun Yan, Kai Chen^*, Hang Geng, Wenqian Fan, Xinrui Zhou

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1345-1379, 2023, DOI:10.32604/cmes.2023.027252

Abstract With increasing global concerns about clean energy in smart grids, the detection of power quality disturbances (PQDs) caused by energy instability is becoming more and more prominent. It is well acknowledged that the PQD effects on power grid equipment are destructive and hazardous, which causes irreversible damage to underlying electrical/electronic equipment of the concerned intelligent grids. In order to ensure safe and reliable equipment implementation, appropriate PQD detection technologies must be adopted to avoid such adverse effects. This paper summarizes the newly proposed and traditional PQD detection techniques in order to give a quick start More > Graphic Abstract

Abdul Quawi^1,*, Y. Mohamed Shuaib¹, M. Manikandan²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3469-3486, 2023, DOI:10.32604/iasc.2023.035001

Abstract In this work, an Artificial Neural Network (ANN) based technique is suggested for classifying the faults which occur in hybrid power distribution systems. Power, which is generated by the solar and wind energy-based hybrid system, is given to the grid at the Point of Common Coupling (PCC). A boost converter along with perturb and observe (P&O) algorithm is utilized in this system to obtain a constant link voltage. In contrast, the link voltage of the wind energy conversion system (WECS) is retained with the assistance of a Proportional Integral (PI) controller. The grid synchronization is… More >

Feng Zhao^1,2, Di Liao^1,*, Xiaoqiang Chen^1,2, Ying Wang^1,2

Energy Engineering, Vol.120, No.5, pp. 1133-1148, 2023, DOI:10.32604/ee.2023.025900

Abstract Aiming at the problems of multiple types of power quality composite disturbances, strong feature correlation and high recognition error rate, a method of power quality composite disturbances identification based on multi-resolution S-transform and decision tree was proposed. Firstly, according to IEEE standard, the signal models of seven single power quality disturbances and 17 combined power quality disturbances are given, and the disturbance waveform samples are generated in batches. Then, in order to improve the recognition accuracy, the adjustment factor is introduced to obtain the controllable time-frequency resolution through multi-resolution S-transform time-frequency domain analysis. On this… More >