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- 实验方案
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Soil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)
摘要： Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.
关键词： precision agriculture,LIBS,PLS regression,gaussian processes,soil,lasso,nutrients
更新于2025-09-16 10:30:52
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Enhanced state estimation and bad data identification in active power distribution networks using photovoltaic power forecasting
摘要： In view of the problems of insu?cient real-time measurements in active distribution networks, a state estimation method for active distribution networks is proposed based on the forecasting of photovoltaic (PV) power generation. First, the extreme learning machine (ELM) enhanced by the genetic algorithm (GA) is used to forecast the PV power generation. Second, the Gaussian mixture model (GMM) is used to model the forecasting error. The weighted mean of the forecasting error is used to correct the forecasting value of the PV power generation, and the weighted variance of the forecasting error is used as the basis for setting the pseudo measurement weight. Finally, the real-time measurements collected by the supervisory control and data acquisition (SCADA) system, the forecasted pseudo measurements, and the virtual measurements are used to estimate the state of the active distribution network using the weighted least square (WLS) algorithm. Through simulations in the IEEE 33-bus system, it is shown that the proposed model provides accurate and reliable pseudo measurements for the active distribution network, improves the redundancy of the system, and thus further improves the accuracy of the state estimation and the capability of detecting and identifying bad data in active distribution systems without adding measurement devices.
关键词： Gaussian mixture model,Bad data,Forecasting of photovoltaic power generation,Active distribution system,State estimation,Pseudo measurement
更新于2025-09-16 10:30:52
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An Automatic Deconvolution Method for Modified Gaussian Model using the Exchange Monte Carlo Method: Application to Reflectance Spectra of Synthetic Clinopyroxene
摘要： Deconvolution analysis of reflectance spectra has been a useful method to infer mineral composition and crystal structure. Many of the recent deconvolution analyses of reflectance spectra of major rock-forming minerals, such as olivine and pyroxene, have been based on a modified Gaussian Model (MGM). The numerical algorithm of the widely used MGM, however, utilizes the steepest descent method, which has a local minima problem. With inaccurate initial parameters, the steepest descent method converges into a local minimum, thus the analyzer must manually adjust initial parameters and calculate the model repeatedly to obtain the desired solution. In order to avoid the local minimum problem, we utilized Bayesian spectral deconvolution with the exchange Monte Carlo method, which is an improved algorithm of the Markov chain Monte Carlo method, aimed to both avoid local minima traps and remove the arbitrariness originated from initial parameters. We applied the model to visible to near infrared reflectance spectra of 31 synthetic clinopyroxene samples with wide ranging Mg, Fe and Ca compositions (solid solution). We obtained results consistent with the previous studies based on conventional MGM analyses, suggesting that the exchange Monte Carlo method can yield results consistent with the conventional MGM analyses purely based on the observed data. We also find that the center wavelengths of 1 μm absorption bands of high-Ca pyroxene samples have a linear dependence on Fe/Mg component. Both 1 μm and 2 μm absorption bands seem to follow approximation lines in the three-dimensional spaces of center wavelengths, Ca and Fe components. The successful application of the exchange Monte Carlo method to a wide range of clinopyroxenes would have a potential to expand the applicability of MGM to a variety of space/ground-based observations, especially when we cannot rely on prior information of the mineralogy.
关键词： Modified Gaussian model,Reflection spectroscopy,Pyroxene,Spectral deconvolution,Monte Carlo method,Synthetic mineral
更新于2025-09-16 10:30:52
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Low Complexity Dimensioning of Sustainable Solar-enabled Systems: A Case of Base Station
摘要： Solar-enabled systems are becoming popular for provisioning pollution-free and cost-effective energy solution. Dimensioning of a solar-enabled system requires estimation of appropriate size of photovoltaic (PV) panel as well as storage capacity while satisfying a given energy outage constraint. Dimensioning has strong impact on the user’s quality of experience and network operator’s interest in terms of energy outage and revenue. In this paper, dimensioning problem of solar-enabled communication nodes is analyzed in order to reduce the computation overhead, where stand-alone solar-enabled base station (SS-BS) is considered as a case study. For this purpose, hourly solar data of last ten years has been taken into consideration for analysis. First, the power consumption model of BS is revised to save energy and increase revenue. Using the hourly solar data and power consumption profile, the lower bounds on panel size and storage capacity are obtained using Gaussian mixture model, which provides a reduced search space for cost-optimal system dimensioning. Then, the cost function and energy outage probability are modeled as functions of panel size and number of battery units using curve fitting technique. The cost function is proven to be quasiconvex, whereas energy outage probability is proven to be convex function of panel size and number of battery units. These properties transform the cost-optimal dimensioning problem into a convex optimization framework, which ensures a global optimal solution. Finally, a Computationally-efficient Energy outage aware Cost-optimal Dimensioning Algorithm (CECoDA) is proposed to estimate the system dimension without requiring exhaustive search. The proposed framework is tested and validated on solar data of several cities; for illustration purpose, four cities, New Delhi, Itanagar, Las Vegas, and Kansas, located at diverse geographical regions, are considered. It is demonstrated that, the presented optimization framework determines the system dimension accurately, while reducing the computational overhead up to 94% and the associated energy requirement for computation with respect to the exhaustive search method used in the existing approaches. The proposed framework CECoDA takes advantage of the location-dependent unique solar profile, thereby achieving cost-efficient solar-enabled system design in significantly less time.
关键词： computation efficiency,cost-optimal system dimensioning,Sustainable solar-enabled system,solar energy harvesting,energy outage,Gaussian mixture model,convex optimization,curve fitting
更新于2025-09-12 10:27:22
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A Hybrid Probabilistic Estimation Method for Photovoltaic Power Generation Forecasting
摘要： Because of stochastic nature of weather conditions, the predictability of photovoltaic (PV) power generation is poor. Compared with the point prediction, the probabilistic prediction of PV power generation can provide more information about the underlying uncertainties, which is beneficial to the stability and safety of grid dispatching and power system. Based on random forest (RF), fuzzy C-means (FCM), sparse Gaussian process (SPGP), improved grey wolf optimizer (IMGWO) algorithm, a hybrid probabilistic estimation method, in this paper, is proposed to predict the probability of PV power generation for every hour in one day. RF algorithm is firstly used to reduce multidimensional input variables. And according to the weather patterns, FCM method is adopted to divide data and get the similar samples. Finally, a hybrid forecasting method combines SPGP and IMGWO is applied to forecast the test data. With the simulation and experimental results, the validity and reliability of the proposed model (IMGWOSP) is verified. The results show that the proposed model has improved both accuracy and practicability, so the stability and safety of grid dispatching and power system can be improved.
关键词： PV power forecast,Spare Gaussian process regression,Probability prediction,Improved grey wolf optimizer algorithm
更新于2025-09-12 10:27:22
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Tolerance Analysis for Piston and Tilt Error in Hexagonal Laser Phased Array
摘要： Coherent Beam Combining is an alternative approach to the construction of high-power lasers, which mitigates the thermo-optic problems occurring in the classic laser construction. However, phased array requires the control of a larger number of parameters, which results in easier beam quality degradation. The most important are phase mismatch (piston error) and tilt error, which cause energy spreading into the side lobes and distortion of the main lobe in far-field intensity pattern. To achieve effective combining, piston and tilt error must be controlled with accuracy to fraction of wavelength. We present numerical model of coherent beam combining of 2D array of laser beams. The analysis of beam combining quality for hexagonal array with seven elements in dependence on Super-Gaussian SGp beam profile for tilt and piston error have been presented. We have taken the tolerance limit as a decrease in Strehl ratio (SR) by 20% for piston and tilt error. Additionally for tilt error as tolerance limit we have taken pointing RMS error equal to diffraction limit 1.5λf/D. Our analysis results in two conclusions. Firstly, the tilt error has higher influence on degradation of beam quality. Secondly, Gaussian beam (p=1) has higher tolerance for both errors than top-hat (p=32).
关键词： tilt error,piston error,hexagonal array,Coherent Beam Combining,Strehl ratio,Super-Gaussian beam profile
更新于2025-09-12 10:27:22
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Design and Simulation of the Fourier Transform Beam Propagation Method in Different Optical Waveguides
摘要： Fundamentals of optical waveguides is a needed resource for any researcher, concerned in optics and communications engineering. Interested by designing or actively running with optical gadgets have to have a company hold close of the standards of light wave propagation. This paper presents an FFT Beam Propagation Method Models for optical waveguides. The technique is based on the use of the Propagation of a Gaussian pulse by a waveguide with a rectangular, triangular optical waveguides and free space the cases of straight and bent optical waveguides are successively considered.
关键词： Gaussian pulse,free space,triangular optical waveguides,optical waveguides,FFT Beam Propagation Method,rectangular
更新于2025-09-12 10:27:22
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Revisiting the calculation of performance margins in monitoring-enabled optical networks
摘要： In the context of future intelligent optical networks, dedicated learning techniques can be employed to monitor physical system parameters with a guaranteed accuracy. In this work, we investigate a method that establishes the link between input parameter uncertainties and the overall performance uncertainty. To this end, neglecting stochastic effects and focusing on the input parameters of a simplified Gaussian noise model version, we employ uncertainty propagation to evaluate the overall performance uncertainty from input parameter uncertainties, and we propose a simple way to link performance uncertainty to margins. With this method, as opposed to direct performance monitoring, it is possible to trace, in a predictable way, the path from the cause (input parameter uncertainties) to the effect (performance uncertainty) and to the additional network-level consequences (performance margins). We briefly review methods used in the literature to set margins in classical systems, and we show how all methods can be unified by means of the correlation between input parameters. By quantifying the impact of input parameter correlations, we further discuss the margins that can be saved if input parameters are partially correlated or uncorrelated, compared to a scenario in which parameters are fully correlated. We finally illustrate the separate impact of each parameter on performance uncertainty, and we briefly discuss their order of importance as a function of the system operating regime and propagated distance.
关键词： optical networks,performance margins,deterministic margins,uncertainty propagation,Gaussian noise model
更新于2025-09-12 10:27:22
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Effects of plasma electron temperature and magnetic field on the propagation dynamics of Gaussian laser beam in weakly relativistic cold quantum plasma
摘要： Self-focusing of Gaussian laser beam has been investigated in quantum plasma under the effect of applied axial magnetic field. The nonlinear differential equation has been derived for studying the variations in the beam-width parameter. The effect of initial plasma electron temperature and the axial magnetic field on self-focusing and normalized intensity are studied. Our investigation reveals that normalized intensity increases to tenfolds where quantum effects are dominant. The normalized intensity further increases to twelvefolds on increasing the magnetic field.
关键词： electron temperature,weakly relativistic,Gaussian,self-focusing,Cold quantum plasma
更新于2025-09-12 10:27:22
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Nonlinear Fiber Optics || Group-velocity dispersion
摘要： The preceding chapter showed how the combined effects of group-velocity dispersion (GVD) and self-phase modulation (SPM) on optical pulses propagating inside a fiber can be studied by solving a pulse-propagation equation. Before considering the general case, it is instructive to study the effects of GVD alone. This chapter considers the pulse-propagation problem by treating fibers as a linear optical medium. In Section 3.1 we discuss the conditions under which the GVD effects dominate over the nonlinear effects by introducing two length scales associated with GVD and SPM. Dispersion-induced broadening of optical pulses is considered in Section 3.2 for several specific pulse shapes, including Gaussian and 'sech' pulses. The effects of initial frequency chirping are also discussed in this section. Section 3.3 is devoted to the effects of third-order dispersion on pulse broadening. An analytic theory capable of predicting dispersive broadening for pulses of arbitrary shapes is also given in this section. We discuss in Section 3.4 how the GVD can limit the performance of optical communication systems and how the technique of dispersion management can be used to combat such limitations.
关键词： dispersion management,dispersion-induced broadening,sech pulses,Group-velocity dispersion,GVD,optical pulses,third-order dispersion,SPM,Gaussian pulses,self-phase modulation,fiber propagation,frequency chirping
更新于2025-09-12 10:27:22