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- 摘要
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Wildfire Risk Assessment Using Multi-Source Remote Sense Derived Variables
摘要： This study focuses on the forest fire risk assessing using entirely remote sensing derived variables. These variables include Fuel moisture content (FMC), Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Elevation and Slope. The Difference and Anomaly of FMC in time series are also calculated since FMC is one of the critical factors in assessing the wildfire risk. The logistic regression model is used to integrate all the variables in the fire occurred and none-occurred areas to derive the Fire Risk Index (FRI). A case study of the above methodology is applied to assess the FRI in Yunnan Province in China. The result shows that the AUC is to 0.8 for grassland and 0.81 for woodland, which indicates the good performance of the presented methodology in assessing forest fire risk.
关键词： forest fire risk,logistic regression model,Forest fire
更新于2025-09-23 15:23:52
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[IEEE 2019 IEEE 13th International Conference on ASIC (ASICON) - Chongqing, China (2019.10.29-2019.11.1)] 2019 IEEE 13th International Conference on ASIC (ASICON) - Design of High-Speed Drivers for 56Gb/s PAM4 Optical Communications in CMOS
摘要： We investigate the feasibility of estimating the total energy expenditure (TEE) of a human for walking/running activities with micro-Doppler signatures. Doppler radar can capture micro-Doppler signatures produced from limb motions when a human moves. As the micro-Doppler signatures contain information regarding limb movement, TEE can be estimated by analyzing the Doppler spectrogram. To understand the relationship between the TEE and micro-Doppler signatures, basic arm and leg motions are measured by the Doppler radar, whereas a respiratory gas analyzer measures the volume of exchanged respiratory gas (O2 and CO2) to obtain a reference TEE. The area of micro-Doppler signatures in a spectrogram has been suggested to serve as key information to estimate TEE. For the verification of the suggested approach, TEE was measured for seven human subjects, who performed walking and running activities on a treadmill at five different speeds using both the Doppler radar and the respiratory gas analyzer. We confirm that strong correlations exist between the micro-Doppler area and the TEE. Finally, a regression model for walking and running activities is developed for a person. Then, the model calculates the TEE under two scenarios, and we find that the estimation errors are 13.2% and 12.3%.
关键词： total energy expenditure,regression model,Human activity monitoring,micro-Doppler,indirect calorimetry
更新于2025-09-23 15:19:57
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Quantitative Analysis of Cadmium Content in Tomato Leaves Based on Hyperspectral Image and Feature Selection
摘要： In order to ensure that safe and healthy tomatoes can be provided to people, a method for quantitative determination of cadmium content in tomato leaves based on hyperspectral imaging technology was put forward in this study. Tomato leaves with seven cadmium stress gradients were studied. Hyperspectral images of all samples were firstly acquired by the hyperspectral imaging system, then the spectral data were extracted from the hyperspectral images. To simplify the model, three algorithms of competitive adaptive reweighted sampling (CARS), variable combination population analysis (VCPA) and bootstrapping soft shrinkage (BOSS) were used to select the feature wavelengths ranging from 431 to 962 nm. Final results showed that BOSS can improve prediction performance and greatly reduce features when compared with the other two selection methods. The BOSS model got the best accuracy in calibration and prediction with R2c of 0.9907 and RMSEC of 0.4257mg/kg, R2p of 0.9821, and RMSEP of 0.6461 mg/kg. Hence, the method of hyperspectral technology combined with the BOSS feature selection is feasible for detecting the cadmium content of tomato leaves, which can potentially provide a new method and thought for cadmium content detection of other crops.
关键词： Regression model,Feature selection,Tomato leaves,Hyperspectral image technology,Non-destructive analysis
更新于2025-09-19 17:15:36
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Line-to-Line Faults Detection for Photovoltaic Arrays Based on I-V Curve Using Pattern Recognition
摘要： In this paper, an identi?cation problem for nonlinear models is explored and a novel fuzzy identi?cation method based on the ant colony optimization algorithm is proposed. First, a modi?ed cluster validity criterion with a fuzzy c-regression model is adopted to ?nd appropriate rule numbers of the Takagi-Sugeno fuzzy model. Then, the ant colony optimization algorithm is adopted and the sifted initial membership function and the consequent parameters of the fuzzy model are obtained. Through an improved fuzzy c-regression model and the orthogonal least-squares method, the premise structure and the consequent parameters can be obtained to establish the Takagi-Sugeno fuzzy model. Some examples are illustrated to show that the proposed method provides better approximation results and robustness than those obtained using some of the existing methods.
关键词： Takagi-Sugeno fuzzy model,Fuzzy system identi?cation,ant colony optimization algorithm (ACO),fuzzy c-regression model
更新于2025-09-19 17:13:59
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Peak Detection Based on FPGA Using Quasi-Newton Optimization Method for Femtosecond Laser Ranging
摘要： In this paper, an identi?cation problem for nonlinear models is explored and a novel fuzzy identi?cation method based on the ant colony optimization algorithm is proposed. First, a modi?ed cluster validity criterion with a fuzzy c-regression model is adopted to ?nd appropriate rule numbers of the Takagi-Sugeno fuzzy model. Then, the ant colony optimization algorithm is adopted and the sifted initial membership function and the consequent parameters of the fuzzy model are obtained. Through an improved fuzzy c-regression model and the orthogonal least-squares method, the premise structure and the consequent parameters can be obtained to establish the Takagi-Sugeno fuzzy model. Some examples are illustrated to show that the proposed method provides better approximation results and robustness than those obtained using some of the existing methods.
关键词： ant colony optimization algorithm (ACO),Takagi-Sugeno fuzzy model,fuzzy c-regression model,Fuzzy system identi?cation
更新于2025-09-19 17:13:59
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Multielectron Effect for High-Order Harmonic Generation From Molecule Irradiated by Bichromatic Counter-Rotating Circularly Polarized Laser Pulses
摘要： In this paper, an identi?cation problem for nonlinear models is explored and a novel fuzzy identi?cation method based on the ant colony optimization algorithm is proposed. First, a modi?ed cluster validity criterion with a fuzzy c-regression model is adopted to ?nd appropriate rule numbers of the Takagi-Sugeno fuzzy model. Then, the ant colony optimization algorithm is adopted and the sifted initial membership function and the consequent parameters of the fuzzy model are obtained. Through an improved fuzzy c-regression model and the orthogonal least-squares method, the premise structure and the consequent parameters can be obtained to establish the Takagi-Sugeno fuzzy model. Some examples are illustrated to show that the proposed method provides better approximation results and robustness than those obtained using some of the existing methods.
关键词： fuzzy c-regression model,Fuzzy system identi?cation,ant colony optimization algorithm (ACO),Takagi-Sugeno fuzzy model
更新于2025-09-19 17:13:59
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Smart solar photovoltaic panel cleaning system
摘要： With the increasing demand for renewable energy, solar photovoltaic technology is being a topic of concern. However, due to the accumulation of dust and dirt over the panel surface, the performance of the photovoltaic system degrades to a noticeable number. To address this issue: a fully automated, cost worthy and efficient system needs to be invented. This paper presents the design and fabrication process of a prototype able to clean the panel surface. The prototype of this system comprises of a cleaning robot and a cloud interface: the cleaning robot is mobile and able to clean the entire solar array back and forth, with its separately driven cleaning rotatory brush; whereas, the cloud interface is a human-machine interface featuring the distant monitoring and control of the robot. Additionally, to notify the performance of distantly placed solar farm, a sensing unit consisting of sensors was added to this system. Furthermore, to add an automatic cleaning feature, a month-long data of totally clean and dusty panel was processed with regression analysis, and the developed regression model was programmed into the sensing unit. The sensing unit added with the regression model is named as an autonomous unit, as it predicts the suitable time for cleaning action. According to the system evaluation done on a demonstration PV module, it was found that the designed system can clean dry dust accumulated over the panel’s surface. Moreover, by attaching the metal rail tracks on a long solar array, the system seems to be implementable on a large scale solar farm.
关键词： Solar Photovoltaics,Distant Monitoring,Regression Model,Robot
更新于2025-09-19 17:13:59
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Parametric Analysis of High Power Disk Laser Welding of 5052-H32 Aluminium Alloy
摘要： High power disk laser conducting welding of 2 mm thick AA 5052-H32 was performed within a process window and optimized for improved weld quality (i.e. penetration depth). The macrostructure of the weldment was investigated for the weld penetration depth at varying processing parameters using stereo zoom optical microscopy. The significance of the single effects and interaction effects of the parameters on the weld penetration depth was determined using ANOVA. Maximum weld penetration depth (1.71 mm) was achieved at laser power of 2600 W, welding speed of 0.03 m/s and focal position of -3.75 mm. At 95% confidence, only the welding speed –focal position interaction was found to contribute significantly to the weld penetration depth. The effect of the welding speed was most noticeable at low focal position (F < -3.9), that is, when the workpiece is further away from the focus. A linear regression mathematical model predicting the penetration depth of AA 5052-H32 disk laser weldments to an accuracy of 86% was developed and validated.
关键词： AA 5052-H32 Aluminium Alloy,Optimisation,Regression Model,Disk Laser Welding,ANOVA,Penetration Depth
更新于2025-09-16 10:30:52
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Experimental study of Hole Taper in Laser Trepan Drilling of Nickel Based Super alloy Sheet
摘要： This research article reports the optimum laser drilling input parameter for getting minimum hole taper and experimentally investigates the behaviour of hole taper in selected laser drilling input parameters on Inconel -718 sheet. Inconel -718 is nickel based super alloy, has diverse application in the field of manufacturing industries, including aerospace, aircraft, automotive, medical equipments, food service equipments and many others. The material is well suited for applications requiring high strength in temperature ranges from cryogenic up to 1400°F. Inconel-718 also exhibits excellent tensile and impact strength. The conventional drilling process faces difficulties to drill quality and precise holes in advanced materials due to its better mechanical properties. Making geometrical better hole is major concerned with conventional drilling process. With the help of Laser drilling process, a geometrically and dimensionally improved hole may be produced. The geometry of hole can be made further better if operating the Laser system at optimum parameters level. In this paper the effects of laser input parameters on hole taper have been investigated and optimal value of input parameters for reduced hole taper has been suggested. The experiments have been conducted by varying one parameter at a time. The experimental data are used to develop the multi regression model for hole taper. A reliable multi regression model is developed for hole taper and modern optimization tool, Genetic algorithm (GA) is used for optimization of the kerf taper. The optimal value of studied laser input parameters such as assist gas pressure, laser Current, stand-off distance, and cutting speed (Trepanning speed) have been suggested for getting lower value of hole taper. Finally, the effects of each laser input parameter of the kerf taper has been discussed.
关键词： Hole Taper,Laser Trapan Drilling,Inconel-718,Regression model,Genetic Algorithm
更新于2025-09-12 10:27:22
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Consistent Regression of Biophysical Parameters with Kernel Methods
摘要： This paper introduces a novel statistical regression framework that allows the incorporation of consistency constraints. A linear and nonlinear (kernel-based) formulation are introduced, and both imply closed-form analytical solutions. The models exploit all the information from a set of drivers while being maximally independent of a set of auxiliary, protected variables. We successfully illustrate the performance in the estimation of chlorophyll content.
关键词： consistency,regression,model inversion,vegetation monitoring,kernel methods
更新于2025-09-10 09:29:36