Previous studies have primarily focused on the extraction of highland barley crops using single phenological images, which ignored the selection of the optimal phenological period for classification. Utilizing the multiple phenological images from Se...
Stock index prediction plays an important role in the creation of better investment strategies. However, prediction can be difficult due to the random fluctuation of financial time series. In pursuit of improved stock index prediction, a hybrid predi...
With the widespread use of the Internet, network security issues have attracted more and more attention, and network intrusion detection has become one of the main security technologies. As for network intrusion detection, the original data source al...
Accurate measurement of forest growing stem volume (GSV) is important for forest resource management and ecosystem dynamics monitoring. Optical remote sensing imagery has great application prospects in forest GSV estimation on regional and global sca...
The fault feature extraction of gearbox is difficult to achieve under complex working conditions, and this paper presents a hybrid fault diagnosis method for gearbox based on the combining product function (CPF) and multipoint optimal minimum entropy...
Estimation of the canopy water content (CWC) is extremely important for irrigation management decisions. Machine learning and hyperspectral imaging technology have provided a potentially useful tool for precise measurement of plant water content. The...
Spatial distribution prediction of growing stock volume (GSV) for supporting the sustainable management of forest ecosystems, is one of the most widespread applications of remote sensing. For this purpose, remote sensing data were used as predictor v...
Sustainability can achieve a balance among economic prosperity, social equity, and environmental protection to ensure the sustainable development and happiness of current and future generations; photovoltaic (PV) power, as a clean, renewable energy,...
Noninvasive blood pressure estimation is crucial for cardiovascular and hypertension patients. Cuffless-based blood pressure estimation has received much attention recently for continuous blood pressure monitoring. This paper proposes a new methodolo...
Accurate and timely acquisition of the spatial distribution of mangrove species is essential for conserving ecological diversity. Hyperspectral imaging sensors are recognized as effective tools for monitoring mangroves. However, the spatial complexit...
Feature selection is a very important direction for network intrusion detection. However, current feature selection technology of network intrusion detection has the problems of low detection rate and low accuracy due to feature redundancy. An improv...
Aiming at the problem that the vibration signals of rolling bearings in high-speed rail traction motors are often affected by noise when they are in a fault state, which makes it very difficult to extract the fault features during fault diagnosis and...
Due to the inherent limitations in remote sensing image quality, seasonal variations, and radiometric inconsistencies, river extraction based on remote sensing image classification often results in omissions. These challenges are particularly pronoun...
Soil organic matter (SOM) is one of the main sources of plant nutrition and promotes plant growth and development. The content of SOM varies in different areas of the field. In this study, a method based on pyrolysis and electronic nose combined with...
The quick and precise assessment of rice distribution by remote sensing technology is important for agricultural development. However, mountain rice is limited by the complex terrain, and its distribution is fragmented. Therefore, it is necessary to...
In this paper, a gait classification method based on the deep belief network (DBN) optimized by the sparrow search algorithm (SSA) is proposed. The multiple features obtained based on surface electromyography (sEMG) are fused. These functions are use...
The estimation of forest above-ground biomass (AGB) can be significantly improved by leveraging remote sensing (RS) and deep learning (DL) techniques. In this process, it is crucial to obtain appropriate RS features and develop a suitable model. Howe...
As a polarimetric synthetic aperture radar (SAR) mode capable of simultaneously acquiring abundant surface information and conducting large-width observations, compact polarimetric synthetic aperture radar (CP SAR) holds great promise for mangrove dy...
The composition and spatial distribution of tree species are pivotal for biodiversity conservation, ecosystem productivity, and carbon sequestration. However, the accurate classification of tree species in subtropical forests remains a formidable cha...
Rapidly increasing numbers of the plastic-covered greenhouse (PCG) worldwide ensure food security but threaten environmental security; thus, accurate monitoring of the spatiotemporal pattern in plastic-covered greenhouses (PCGs) is necessary for mode...
The IDH somatic mutation status is an important basis for the diagnosis and classification of gliomas. We proposed a “6-Step” general radiomics model to noninvasively predict the IDH mutation status by simultaneously tuning combined multi...
Plastic waste accumulation presents critical environmental challenges demanding innovative circular economy solutions. This study developed a comprehensive machine learning framework to systematically identify optimal enzyme combinations for polyeste...
Sea ice drift strongly influences sea ice thickness distribution and indirectly controls air-sea ice-ocean interactions. Estimating sea ice drift over a large range of spatial and temporal scales is therefore needed to characterize the properties of...
Feature selection is a way of reducing the features of data such that, when the classification algorithm runs, it produces better accuracy. In general, conventional feature selection is quite unstable when faced with changing data characteristics. It...
The problem of data classification or data fitting is widely applicable in a multitude of scientific areas, and for this reason, a number of machine learning models have been developed. However, in many cases, these models present problems of overfit...
Brain tumors and other nervous system cancers are among the top ten leading fatal diseases. The effective treatment of brain tumors depends on their early detection. This research work makes use of 13 features with a voting classifier that combines l...
Tree species classification is crucial for forest resource investigation and management. Remote sensing images can provide monitoring information on the spatial distribution of tree species and multi-feature fusion can improve the classification accu...
Design of low-density SNP chips provides an opportunity for wide application of genomic selection at lower cost. A novel strategy referred to as the “block-free” method is proposed in this study to select a subset of SNPs from a high-dens...
Mineral exploiting information is an important indicator to reflect regional mineral activities. Accurate extraction of this information is essential to mineral management and environmental protection. In recent years, there are an increasingly large...
Location-based services provide significant economic and social benefits. The ubiquity, low cost, and accessibility of geomagnetism are highly advantageous for localization. However, the existing geomagnetic localization methods suffer from location...
Africa has the largest grassland area among all grassland ecosystems in the world. As a typical agricultural and animal husbandry country in Africa, animal husbandry plays an important role in this region. The investigation of grassland resources and...
Accurate crop mapping is vital for monitoring agricultural resources, food security, and ecosystem sustainability. Advances in high-resolution sensing technologies now enable precise, large-scale crop mapping, improving agricultural management and de...
Breast Cancer (BC) detection and classification are critical tasks in medical diagnostics. The lives of patients can be greatly enhanced by the precise and early detection of BC. This study suggests a novel approach for detecting BC that combines dee...
A photovoltaic array fault diagnosis method based on an improved honey badger optimization algorithm is proposed to improve the accuracy of photovoltaic array fault diagnosis. Firstly, analyze the current and power output characteristic curves of the...
Epilepsy is a neurological disorder that is characterized by transient and unexpected electrical disturbance of the brain. Seizure detection by electroencephalogram (EEG) is associated with the primary interest of the evaluation and auxiliary diagnos...
Slope entropy (Slopen) has been demonstrated to be an excellent approach to extracting ship-radiated noise signals (S-NSs) features by analyzing the complexity of the signals; however, its recognition ability is limited because it extracts the featur...
Most research on forest tree species classification based on optical image data uses information such as spectral reflectance, vegetation index, texture, and phenology data. However, owing to the limited spectral resolution of multispectral images an...
This study suggests a hybrid approach that combines improved feature selection and intelligent diagnosis to increase the operational safety and intelligent diagnosis capabilities of hydropower units. In order to handle the vibration data, complete en...
The On-Load Tap Changer (OLTC) is the only movable mechanical component in a converter transformer. To ensure the reliable operation of the OLTC and to promptly detect mechanical faults in OLTCs to prevent them from developing into electrical faults,...
Feature selection is a preprocessing step for various classification tasks. Its objective is to identify the most optimal features in a dataset by eliminating redundant data while preserving the highest possible classification accuracy. Three improve...
This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover m...
This paper addresses the challenge of optimizing end-to-end neural diarization systems for conversational telephone speech, focusing on diverse acoustic features beyond traditional Mel-filterbanks. We present a methodological framework for integratin...
Multispectral remote sensing (RS) data and synthetic aperture radar (SAR) data can provide horizontal and vertical information about forest AGB under different stand conditions. With the abundance of RS features extracted from multispectral and SAR d...
Garlic, as an important economic crop, plays a crucial role in the global agricultural production system. Accurate identification of garlic cultivation areas is of great significance for agricultural resource allocation and industrial development. Tr...
Accurate regional-scale mapping of soil organic matter (SOM) is crucial for land productivity management and global carbon pool monitoring. Current remote sensing inversion of SOM faces challenges, including the underutilization of temporal informati...
Object-based image analysis allows several different features to be calculated for the resulting objects. However, a large number of features means longer computing times and might even result in a loss of classification accuracy. In this study, we u...
Timely and accurate acquisition of crop planting areas and spatial distribution are deemed essential for grasping food configurations and guiding agricultural production. Despite the increasing research on crop mapping and changes with the developmen...
Timely and accurate land use information in open-pit mines is essential for environmental monitoring, ecological restoration planning, and promoting sustainable progress in mining regions. This study used high-resolution unmanned aerial vehicle (UAV)...
Defocus blur is often encountered in images taken with optical imaging equipment. It might be unwanted, but it might also be a deliberate artistic effect, which means it might help how we see the scenario in an image. In specific applications like im...
Turbulence is a significant operational aviation safety hazard during all phases of flight. There is an urgent need for a method of airline turbulence identification in aviation systems to avoid turbulence hazards to aircraft during flight. Integrati...
of 118