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Improved deep mixed kernel randomized network for wind speed prediction

Clean Energy 2023年第5期7卷 1006-1031页

作者： Vijaya krishna Rayi Ranjeeta Bisoi S.p.Mishra p.k.dash Department of EEE GMR Institute of TechnologyRajamAndhra PradeshIndia Multidisciplinary Research Cell Siksha‘O’Anusandhan Deemed to be UniversityBhubaneswarOdishaIndia

Forecasting wind speed is an extremely complicated and challenging problem due to its chaotic nature and its dependence on several atmospheric *** there are several intelligent techniques in the literature for wind speed prediction,their accuracies are not yet very ***,in this paper,a new hybrid intelligent technique named the deep mixed kernel random vector functional-link network auto-encoder(AE)is proposed for wind speed *** proposed method eliminates manual tuning of hidden nodes with random weights and biases,providing prediction model generalization and representation *** reduces reconstruction error due to the exact inversion of the kernel matrix,unlike the pseudo-inverse in a random vector functional-link network,and short-ens the execution ***,the presence of a direct link from the input to the output reduces the complexity of the prediction model and improves the prediction *** kernel parameters and coefficients of the mixed kernel system are optimized using a new chaotic sine–cosine Levy flight optimization *** lowest errors in terms of mean absolute error(0.4139),mean absolute percentage error(4.0081),root mean square error(0.4843),standard deviation error(1.1431)and index of agreement(0.9733)prove the efficiency of the proposed model in comparison with other deep learning models such as deep AEs,deep kernel extreme learning ma-chine AEs,deep kernel random vector functional-link network AEs,benchmark models such as least square support vector machine,autoregressive integrated moving average,extreme learning machines and their hybrid models along with different state-of-the-art methods.

关键词： deep neural network mixed kernel random vector functional network auto-encoder chaotic sine-cosine Levy flight optimization single and multistep wind speed prediction

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Short Term Wind Speed prediction Using Multiple kernel pseudo Inverse Neural Network

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International Journal of Automation and computing 2018年第1期15卷 66-83页

作者： S.p.Mishra p.k.dash Multi-disciplinary Research Centre (MDRC) Department of Electrical EngineeringSiksha "O" Anusandhan University

An accurate short-term wind speed prediction algorithm based on the efficient kernel ridge pseudo inverse neural network （kRpINN） variants is proposed in this paper. The use of nonlinear kernel functions in pseudo inverse neural networks eliminates the trial and error approach of choosing the number of hidden layer neurons and their activation functions. The robustness of the proposed method has been validated in comparison with other models such as pseudo inverse radial basis function （pIRBF） and Legendre tanh activation function based neural network, i.e., pILNNT, whose input weights to the hidden layer weights are optimized using an adaptive firefly algorithm, i.e., FFA. However, since the individual kernel functions based kRpINN may not be able to produce accurate forecasts under chaotically varying wind speed conditions, a linear combination of individual kernel functions is used to build the multi kernel ridge pseudo inverse neural network （Mk-RpINN） for providing improved forecasting accuracy, generalization, and stability of the wind speed prediction model. Several case studies have been presented to validate the accuracy of the short-term wind speed prediction models using the real world wind speed data from a wind farm in the Wyoming State of USA over time horizons varying from 10 minutes to 5 hours.

关键词： Wind speed prediction pseudo inverse neural network kernel ridge regression nonlinear kernels firefly optimizatiotl.

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A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and pattern Recognition

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International Journal of Automation and computing 2019年第3期16卷 398-412页

作者： N.R.Nayak p.k.dash R.Bisoi Multidisciplinary Research Cell Siksha O Anusandhan University Khandagiri Square

A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference ***,it suffers from heavy computational overhead and large execution *** paper,therefore,uses a novel fast discrete sparse S-transform(SST)suitable for extracting time frequency response to monitor non-stationary signal parameters,which can be ultimately used for disturbance detection,and their pattern *** the sparse S-transform matrix,some relevant features have been extracted which are used to distinguish among different non-stationary signals by a fuzzy decision tree based *** algorithm is robust under noisy *** power quality as well as chirp signals have been simulated and tested with the proposed technique in noisy conditions as *** real time mechanical faulty signals have been collected to demonstrate the efficiency of the proposed *** the simulation results imply that the proposed technique is very much efficient.

关键词： Non-stationary signals sparse S-transform(SST) scaling method fuzzy decision tree pattern classification

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Adaptive fractional integral terminal sliding mode power control of UpFC in DFIG wind farm penetrated multimachine power system

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protection and Control of Modern power Systems 2018年第1期3卷 79-92页

作者： p.k.dash R.k.patnaik S.p.Mishra Siksha O Anusandhan University Khandagiri SquareBhubaneswarOdisha 751030India GMR Institute of Technology RajamAndhra Pradesh 532127India

With an aim to improve the transient stability of a DFIG wind farm penetrated multimachine power system(MpN),an adaptive fractional integral terminal sliding mode power control(AFITSMpC)strategy has been proposed for the unified power flow controller(UpFC),which is compensating the *** proposed AFITSMpC controls the dq-axis series injected voltage,which controls the admittance model(AM)of the *** a result the power output of the DFIG stabilizes which helps in maintaining the equilibrium between the electrical and mechanical power of the nearby *** the rotor angular deviation of the respective generators gets recovered,which significantly stabilizes the *** proposed AFITSMpC for the admittance model of the UpFC has been validated in a DFIG wind farm penetrated 2 area 4 machine power system in the MATLAB *** robustness and efficacy of the proposed control strategy of the UpFC,in contrast to the conventional pI control is vindicated under a number of intrinsic operating conditions,and the results analyzed are satisfactory.

关键词： Adaptive fractional integral terminal sliding mode power control Doubly fed induction generator Multimachine power network Unified power flow controller

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A fast time-frequency response based differential spectral energy protection of AC microgrids including fault location

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protection and Control of Modern power Systems 2017年第1期2卷 331-358页

作者： O.Dharmapandit R.k.patnaik p.k.dash Electrical Engineering Department Institute of Technical Education and ResearchInstitute of Technical Education and ResearchSiksha O Anusandhan UniversityBhubaneswar-751030India. Electrical and Electronics Engineering Department GMR Instittute of TechnologyRajamAndhra Pradesh-532127India.

This paper proposes a pattern recognition based differential spectral energy protection scheme for ac microgrids using a Fourier kernel based fast sparse time-frequency representation(SST or simply the sparse S-Transform).The average and differential current components are passed through a change detection filter,which senses the instant of fault inception and registers a change detection point(CDp).Subsequently,if CDp is registered for one or more phases,then half cycle data samples of the average and differential currents on either side of the CDp are passed through the proposed SST technique,which generates their respective spectral energies and a simple comparison between them detects the occurrence and type of the *** SST technique is also used to provide voltage and current phasors and the frequency during faults which is further utilized to estimate the fault *** proposed technique as compared to conventional differential current protection scheme is quicker in fault detection and classification,which is least effected from bias setting,has a faster relay trip response(less than one cycle from fault incipient)and a better accuracy in fault *** significance and accuracy of the proposed scheme have been verified extensively for faults in a standard microgrid system,subjected to a large number of operating conditions and the outputs vindicate it to be a potential candidate for real time applications.

关键词： Microgrid Differential spectral energy protection Time-frequency representation Fault classification Fault location

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pile foundation in alternate layered liquefiable and non-liquefiable soil deposits subjected to earthquake loading

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 359-376页

作者： praveen Huded M Suresh R dash LEA Associates South East Asia pvt.Ltd. New Delhi 110044India Indian Institute of Technology Bhubaneswar Khurda 752050India

pile foundations are still the preferred foundation system for high-rise structures in earthquake-prone *** foundations have experienced failures in past earthquakes due to *** on pile foundations in liquefiable soils has primarily focused on the pile foundation behavior in two or three-layered soil ***,in natural occurrence,it may occur in alternative layers of liquefiable and non-liquefiable ***,the experimental and/or numerical studies on the layered effect on pile foundations have not been widely addressed in the *** of the design codes across the world do not explicitly mention the effect of sandwiched non-liquefiable soil layers on the pile *** the present study,the behavior of an end-bearing pile in layered liquefiable and non-liquefiable soil deposit is studied *** study found that the kinematic bending moment is higher and governs the design when the effect of the sandwiched non-liquefied layer is considered in the analysis as opposed to when its effect is ***,ignoring the effect of the sandwiched non-liquefied layer in a liquefiable soil deposit might be a nonconservative design approach.

关键词： pile foundation liquefaction alternately layered soil fixity effect layered effect

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Seasonal influence of freshwater discharge on spatio-temporal variations in primary productivity, sea surface temperature, and euphotic zone depth in the northern Bay of Bengal

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Acta Oceanologica Sinica 2024年第6期43卷 1-14页

作者： Hafez Ahmad Felix Jose Md.Simul Bhuyan Md.Nazrul Islam padmanava dash Geosystems Research Institute/Department of Geosciences Mississippi State UniversityStarkville 39759USA Department of Oceanography University of ChittagongChittagong 4331Bangladesh Department of Marine&Earth Sciences Florida Gulf Coast UniversityFort Myers 33965USA Bangladesh Oceanographic Research Institute Cox’s Bazar 4730Bangladesh Faculty of Marine Sciences&Fisheries Institute of Marine SciencesUniversity of ChittagongChittagong 4331Bangladesh Department of Geography and Environment Jahangirnagar UniversityDhaka 1342Bangladesh Department of Geosciences Mississippi State UniversityStarkville 39759USA

Ocean productivity is the foundation of marine food web,which continuously removes atmospheric carbon dioxide and supports life at sea and on ***-temporal variability of net primary productivity(Npp),sea surface temperature(SST),sea surface salinity(SSS),mixed layer depth(MLD),and euphotic zone depth(EZD) in the northern B ay of Bengal(BoB) during three monsoon seasons were examined in this study based on remote sensing data for the period 2005 to *** compare the Npp distribution between the coastal zones and open BoB,the study area was divided into five zones(Z1-Z5).Results suggest that most productive zones Z2 and Zl are located at the head bay area and are directly influenced by freshwater discharge together with riverine sediment and nutrient *** Z1-Z5,the Npp ranges from 5 315.38 mg/(m~2·d) to 346.7 mg/(m~2·d)(carbon,since then the same).The highest monthly average Npp of 5 315.38 mg/(m~2·d) in February and 5 039.36 mg/(m~2·d) in June were observed from Z2,while the lowest monthly average of 346.72 mg/(m~2·d) was observed in March from Z4,which is an oceanic *** values vary from 6-154 m for the study area,and it has an inverse correlation with Npp *** is deeper during the summer season and shallower during the wintertime,with a corresponding increase in *** the year,monthly SST shows slight fluctuation for the entire study area,and statistical analysis shows a significant correlation among Npp,and EZD,overall positive between Npp and MLD,whereas no significant correlation among SSS,and SST for the northern ***-term trends in SST and productivity were significantly po sitive in head bay zones but negatively productive in the open *** findings in this study on the distribution of Npp,SST,SSS,MLD,and EZD and their seasonal variability in five different zones of BoB can be used to further improve the management of marine resources and overall environmental condition in response to climate change

关键词： chlorophyll a sea surface temperature euphotic zone depth primary productivity Ganges-Brahmaputra ocean color Bay of Bengal monsoon

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A Hybrid Machine Learning Approach for Improvised QoE in Video Services over 5G Wireless Networks

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Computers, Materials & Continua 2024年第3期78卷 3195-3213页

作者： k.B.Ajeyprasaath p.Vetrivelan School of Electronics Engineering Vellore Institute of TechnologyChennaiTamil Nadu600127India

Video streaming applications have grown considerably in recent *** a result,this becomes one of the most significant contributors to global internet *** to recent studies,the telecommunications industry loses millions of dollars due to poor video Quality of Experience(QoE)for *** the standard proposals for standardizing the quality of video streaming over internet service providers(ISps)is the Mean Opinion Score(MOS).However,the accurate finding of QoE by MOS is subjective and laborious,and it varies depending on the user.A fully automated data analytics framework is required to reduce the inter-operator variability characteristic in QoE *** work addresses this concern by suggesting a novel hybrid XGBStackQoE analytical model using a two-level layering *** one combines multiple Machine Learning(ML)models via a layer one Hybrid *** ML models at level one are trained using the entire training data *** level two Hybrid XGBStackQoE-Model is fitted using the outputs(meta-features)of the layer one ML *** proposed model outperformed the conventional models,with an accuracy improvement of 4 to 5 percent,which is still higher than the current traditional *** proposed framework could significantly improve video QoE accuracy.

关键词： Hybrid XGBStackQoE-model machine learning MOS performance metrics QoE 5G video services

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MDCN:Modified Dense Convolution Network Based Disease Classification in Mango Leaves

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Computers, Materials & Continua 2024年第2期78卷 2511-2533页

作者： Chirag Chandrashekar k.p.Vijayakumar k.pradeep A.Balasundaram School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia Center for Cyber physical Systems School of Computer Science and EngineeringVellore Institute of Technology(VIT)ChennaiIndia

The most widely farmed fruit in the world is *** the production and quality of the mangoes are hampered by many *** diseases need to be effectively controlled and ***,a quick and accurate diagnosis of the disorders is *** convolutional neural networks,renowned for their independence in feature extraction,have established their value in numerous detection and classification ***,it requires large training datasets and several parameters that need careful *** proposed Modified Dense Convolutional Network(MDCN)provides a successful classification scheme for plant diseases affecting mango *** model employs the strength of pre-trained networks and modifies them for the particular context of mango leaf diseases by incorporating transfer learning *** data loader also builds mini-batches for training the models to reduce training ***,optimization approaches help increase the overall model’s efficiency and lower computing *** employed on the MangoLeafBD Dataset consists of a total of 4,000 *** the experimental results,the proposed system is compared with existing techniques and it is clear that the proposed algorithm surpasses the existing algorithms by achieving high performance and overall throughput.

关键词： Leaf disease detection deep convolutional neural networks transfer learning optimization MangoLeafBD Dataset

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Emission colour tuning in kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)phosphor

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Journal of Rare Earths 2024年第1期42卷 57-65,I0002页

作者： Janani k Gayathri E Vijayatha V Ramasubramanian S Thiyagarajan p Department of Science and Humanities Nehru Institute of TechnologyKaliapuramThirumalayampalayamCoimbatoreIndia Department of Sciences Amrita School of Physical SciencesAmrita Vishwa VidyapeethamCoimbatoreIndia Department of physics Anna UniversityChennaiIndia

kLnF_(4):Yb^(3+),Er^(3+)/Ho^(3+)(Ln=Y,Yb,Gd)phosphors were prepared by solid-state reaction *** each of the Yb^(3+)/Er^(3+)and Yb^(3+)/Ho^(3+)co-doped phosphors independently,phase confirmation and morphological examination were accomplished using the X-ray diffraction technique and scanning electron microscope analysis.X-ray photoelectron spectroscopy analysis shows the charge state and existence of lanthanides and *** luminescence emissions of green and red colour were detected for the synthesized *** changes in the upconverted emission intensities and colour output pertaining to the change of the lanthanide host matrix along with dopants were investigated for the prepared *** the upconversion luminescence,erbium-doped samples exhibit a predominance of red emission while holmium-doped samples display a prevalence of green *** rare-earth Er/Ho doped kYbF4shows strong red emission compared to other ***_(4):Yb,Er/Ho exhibits relatively significant green upconve rsion emissions,while Yb,Er-doped kGdF_(4)host displays a 10-fold increase in green/red emission ratio with an increase in the input power of 20-780 *** photoluminescence studies and decay curve analysis were carried out using UV light excitation for the developed phosphors.A higher lifetime of 2.2 ms was measured for the downshifting red emission in the Ho doped kYbF_(4)*** study suggests a potential for colour tunability in the upconversion and downshifting emissions through host modifications to the fluoride phosphor.

关键词： Rare earths Energy transfer upconversion Downshifting Colour coordinates

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