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Granulation-based LSTm.rF combination model for hourly seasurface temperature prediction

International Journal of Digital earth 2023年第1期16卷 3838-3859页

作者： mengmeng Cao Kebiao mao Sayed m.Bateni Changhyun Jun Jiancheng Shi Yongming Du Guoming Du Hulunbeir Grassland ecosystem.research Station Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijingPeople’s Republic of China State Key Laboratory of remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingPeople’s Republic of China School of Physics and electronic-engineering Ningxia UniversityNingxia University750021China Department of Civil and environmental engineering and Water resources research Center University of Hawaii at Mano1HonoluluHIUSA Department of Civil and environmental engineering College of EngineeringChung-Ang UniversitySeoulSouth Korea National Space Science Center Chinese Academy of SciencesBeijingPeople’s Republic of China School of Public Administration and Law Northeast Agricultural UniversityHarbinPeople’s Republic of China

Accurate predictions of sea surface temperature(SST)are crucial due to the significant impact of SST on the global ocean-atmospheric system and its potential to trigger extreme weather *** existing machine-learning-based ssT predictions adapt the traditional iterative point-wise prediction mechanism,whose predicting horizons and accuracy are limited owing to the high sensitivity to cumulative errors during iterative ***,this paper proposes a novel granulation-based long short-term mem.ry(LsTm)-random forest(rF)combination model that can fully capture the feature dependencies involved in the fluctuation of SsT sequences,reduce the cumulative error in the iteration process,and extend the prediction horizons,which includes two sub-models(adaptive granulation model and hybrid prediction model).They can restack the one-dimensional ssT time-series into multidimensional feature variables,and achieve a strong forecasting *** analysis shows that the proposed model can achieve m.re accurate prediction-hours in nearly all prediction ranges from 1 to 125 *** average prediction error of the proposed model in 25-125 h is 0.07 K,similar to that(0.067 K)in the first 24 h,which exhibits a high generalization performance and robustness and isthus a promising platform for the medium-and long-term forecasting of hourly SSTs.

关键词： SST prediction adaptive granulation method LSTm rF error reciprocal method

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Optimal Sparse Autoencoder Based Sleep Stage Classification Using Biomedical Signals

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Computer Systems Science & engineering 2023年第2期44卷 1517-1529页

作者： Ashit Kum.r Dutta Yasser Albagory manal Al Faraj Yasir A.m.eltahir Abdul rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer engineering College of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of respiratory Care College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

The recently developed machine learning(mL)models have the ability to obtain high detection rate using biomedical ***,this article develops an Optimal Sparse Autoencoder based Sleep Stage Classiﬁcation model on electroencephalography(eeG)Biomedical Signals,named OSAe-SSCeeG *** major intention of the OSAe-SSCeeG technique is toﬁnd the sleep stage disorders using the eeG biomedical *** OSAe-SSCeeG technique prim.rily undergoes preprocessing using min-max data normalization ***,the classiﬁcation of sleep stages takes place using the Sparse Autoencoder with Smoothed regularization(SAe-Sr)with softmax(Sm)***,the parameter optimization of the SAe-Sr technique is carried out by the use of Coyote Optimization Algorithm(COA)and it leads to boosted classiﬁcation efﬁ*** order to ensure the enhanced performance of the OSAe-SSCeeG technique,a wide ranging simulation analysis is performed and the obtained results demonstrate the betterment of the OSAe-SSCeeG tech-nique over the recent methods.

关键词： Biomedical signals eeG sleep stage classiﬁcation machine learning autoencoder softmax parameter tuning

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multi-gradient-direction based deep learning model for arecanut disease identification

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CAAI Transactions on Intelligence Technology 2022年第2期7卷 156-166页

作者： S.B.mallikarjuna Palaiahnakote Shivakum.ra Vijeta Khare m.Basavanna Umapada Pal B.Poornima Department of Computer Science and engineering Bapuji Institute of Engineering and TechnologyDavanagereAffiliated to Visvesvaraya Theological UniversityBelagaviKarnatakaIndia Faculty of Computer Science and Information Technology University of MalayaKuala LumpurMalaysia Adani Institute of Infrastructure engineering AhmedabadIndia Department of Computer Science Davanagere UniversityDavanagereKarnatakaIndia Computer Vision and Pattern recognition Unit Indian Statistical InstituteKolkataWest BengalIndia

Arecanut disease identification is a challenging problem in the field of image *** this work,we present a new combination of multi-gradient-direction and deep con-volutional neural networks for arecanut disease identification,namely,rot,split and *** to the effect of the disease,there are chances of losing vital details in the *** enhance the fine details in the images affected by diseases,we explore multi-Sobel directional masks for convolving with the input image,which results in enhanced *** proposed method extracts arecanut as foreground from the enhanced images using Otsu ***,the features are extracted for foreground information for disease identification by exploring the resNet *** advantage of the proposed approach is that it identifies the diseased images from the healthy arecanut *** results on the dataset of four classes(healthy,rot,split and rot-split)show that the proposed model is superior in terms of classification rate.

关键词： deep learning image analysis pattern recognition

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State Transition Induced by Self-Steepening and Self Phase-modulation

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Chinese Physics Letters 2014年第1期31卷 33-36页

作者： He Jing-Song Xu Shu-Wei m. S. ruderman r. erdélyi Department of mathematics Ningbo University Ningbo 315211 DAmTP University of Cambridge Cambridge CB3 0WA UK School of mathematics University of Science and Technology of China Hefei 230026 Solar Physics and Space Plasma research Centre University of Sheffield Sheffield S3 7RH UK

We present a rational solution for a mixed nonlinear Schr6dinger （mNLS） equation. This solution has two free parameters, a and b, representing the contributions of self-steepening and self phase-modulation （SPm） of an associated physical system, respectively. It describes five soliton states： a paired bright-bright soliton, a single soliton, a paired bright-grey soliton, a paired bright-black soliton, and a rogue wave state. We show that the transition among these live states is induced by self-steepening and SPm through tuning the values of a and b. This is a unique and potentially fundamentally important phenomenon in a physical system described by the mNLS eauation.

关键词： Solitons

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First report of L1014F kdr mutation in Culex quinquefasciatus in mexico

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Insect Science 2016年第6期23卷 829-834页

作者： Gustavo Ponce Iram P. Sanchez Selene m. Garcia Jose m. Torrado Saul Lozano-Fuentes Beatriz Lopez-monroy Adriana e. Flores Facultad de Ciencias Biologicas Universidad Autonoma de Nuevo Leon A v. Universidad sin Cd. Universitaria San Nicolas de los GarzaN.L. 66455 Mexico Department of microbiology Immunology and Pathology Colorado State University Fort Collins CO USA

The L1014F mutation in the voltage-sodium channel gene has been associated with resistance to DDT and pyrethroids in various arthropod species including mosquitoes. We determined the frequency of the L1014F kdr mutation in 16 field populations of Culex quinquefasciatus from Northeastern mexico collected between 2008 and 2013. The L1014F was present in all populations analyzed with the lowest frequency （3.33%） corresponding to the population from monclova collected in 2012, and the highest frequency （63.63%） from the monterrey population collected in 2012. The presence of a kdr mutation in populations of Cx. quinquefasciatus from northeastern mexico provides evidence ofpyrethroid resistance. This requires a special attention, considering that pyrethroid-based insecticides are commonly used in vector-control campaigns, especially against Aedes aegypti （L.）.

关键词： Culex quinquefasciatus insecticide resistance kdr L 1014F mutation

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m5 model Tree to Predict Temporal evolution of Clear-Water Abutment Scour

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Open Journal of Geology 2016年第9期6卷 1045-1054页

作者： r. Biabani m. meftah Halaghi Kh. Ghorbani Department of Water engineering Faculty of Agriculture Tabriz University Tabriz Iran Department of Water engineering Gorgan University of Agricultural Sciences and Natural Resources Gorgan Iran

Scour is a natural phenomenon that is created by the rivers streams or the flood which brings about transferring or eroding of bed materials. To have accurate and safe erosion control structures design, maximum scour depth in downstream of the structures gains specific significance. In the current study, m5 model tree as remedy data mining approaches is suggested to estimate the scour depth around the abutments. To do this, Kayaturk laboratory data (2005), with different hydraulic conditions, are used. Then, the results of m5 model were also compared with genetic programming (GP) and pervious empirical results to investigate the applicability, ability, and accuracy of these procedures. To examine the accuracy of the results yielded from the m5 and GP procedures, two performance indicators (determination coefficient (r2) and root mean square error (rmSe)) were used. The comparison test of results clearly shows that the implementation of m5 technique sounds satisfactory regarding the performance indicators (r2 = 0.944 and rmSe = 0.126) with less deviation from the num.rical values. In addition, m5 tree model, by presenting relationships based on liner regression, has good capability to estimate the depth of scour abutment for engineers in practical terms.

关键词： Abutments Scour Depth m5 model Tree Genetic Programming model (GP)

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enhanced energy efficient with a Trust Aware in mANeT for real-Time Applications

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Computers, materials & Continua 2023年第4期75卷 587-607页

作者： m.V.Narayana Vadla Pradeep Kum.r Ashok Kum.r Nanda Hanumantha rao Jalla Subba reddy Chavva Department of CSe Guru Nanak Institutions Technical CampusHyderabadRanga Reddy DistrictTelangana501506India Department of CSe B V Raju Institute of TechnologyNarsapurMedakTelangana502313India Department of CSe T.R.R.Government Degree College KandukurKandukurA.P.523105India Department of IT VFST&Research(Deemed to be University)VadlamudiA.P.522213India

mobile ad hoc networks (mANeTs) are subjected to attack detectionfor transmitting and creating new messages or existing message *** attacker on another node evaluates the forging activity in themessage directly or indirectly. every node sends short packets in a mANeTenvironment with its identifier, location on the map, and time through *** attackers on the network broadcast the warning message usingfaked coordinates, providing the appearance of a network collision. Similarly,mANeT degrades the channel utilization performance. Performancehighly affects network performance through security algorithms. This paperdeveloped a trust management technique called enhanced Beacon Trustmanagement with Hybrid Optimization (eBTm-Hyopt) for efficient clusterhead selection and malicious node detection. It tries to build trust amongconnected nodes and may im.rove security by requiring every participatingnode to develop and distribute genuine, accurate, and trustworthy materialacross the network. Specifically, optimized cluster head election is done periodicallyto reduce and balance the energy consumption to im.rove the lifetimenetwork. The cluster head election optimization is based on hybridizingParticle Swarm Optimization (PSO) and Gravitational Search OptimizationAlgorithm (GSOA) concepts to enable and ensure reliable routing. Simulationresults show that the proposed eBTm-HYOPT outperforms the state-of-thearttrust model in terms of 297.99 kbps of throughput, 46.34% of PDr, 13%of energy consumption, 165.6 kbps of packet loss, 67.49% of end-to-end delay,and 16.34% of packet length.

关键词： mANeT malicious nodes clustering trust management beacon message

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Linear Active Disturbance rejection Control with a Fractional-Order Integral Action

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Computers, materials & Continua 2022年第11期73卷 3057-3079页

作者： maâm.r Bettayeb rachid mansouri Ubaid m.Al-Saggaf Abdulrahman U.Alsaggaf mohammed moinuddin electrical engineering Department University of SharjahUnited Arab Emirates L2CSP Laboratory University Mouloud Mammeri of Tizi-OuzouAlgeria Center of excellence in Intelligent engineering Systems(CeIeS) King Abdulaziz UniversityJeddahSaudi Arabia electricaland Computer engineering Department King Abdulaziz UniversityJeddahSaudi Arabia

Linear active disturbance rejection control(LADrC)is a powerful control structure thanks to its performance in uncertainties,internal and external disturbances estimation and *** extended state observer(eSO)based controller is the key to the LADrC *** this article,the LADrC scheme combined with a fractional-order integral action(FOILADrC)is proposed to im.rove the robustness of the standard *** the robust closed-loop Bode’s ideal transfer function(BITF),an appropriate pole placement method is proposed to design the set-point tracking controller of the FOI-LADrC *** simulations and experimental results on a cart-pendulum system will illustrate the effectiveness of the proposed FOI-LADrC scheme for the disturbance rejection,the set-point tracking and the im.roved *** illustrate the LADrC control schemes and to verify the performance of the proposed FOI-LADrC,compared to the standard LADrC and IOI-LADrC structures,two tests will be carried ***,simulation tests on an academic example will be presented to show the effect of the different parameters of the control law on the performance of the closed-loop ***,these three control structures are implemented on an experimental test bench,the cart-pendulum system,to show their efficiency and to show the superiority of the proposed method compared to the two other structures.

关键词： Fractional calculus active disturbance rejection control pole placement cart-pendulum system robust control

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An Optimized Deep-Learning-Based Low Power Approximate multiplier Design

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Computer Systems Science & engineering 2023年第2期44卷 1647-1657页

作者： m.Usharani B.Sakthivel S.Gayathri Priya T.Nagalakshmi J.Shirisha Department of electronics and Communication engineering Er.Perunal Manimekalai College of EngineeringKonneripalliHosur635117India Department of electronics and Communication engineering Pandian Saraswathi Yadav Engineering CollegeSivagangaiTamilnadu630561India Department of electronics and Communication engineering R.M.D Engineering CollegeGummidipundiTamilnadu601206India Department of Computer Science and engineering Koneru Lakshmaiah Education FoundationVaddeswaramGuntur522502India Department of electronics and Communication engineering Malla Reddy Engineering CollegeHyderabadTelangana500015India

Approximate computing is a popularﬁeld for low power consumption that is used in several applications like image processing,video processing,multi-media and data *** Approximate computing is majorly performed with an arithmetic circuit particular with a *** multiplier is the most essen-tial element used for approximate computing where the power consumption is majorly based on its *** are several researchers are worked on the approximate multiplier for power reduction for a few decades,but the design of low power approximate multiplier is not so *** seems a bigger challenge for digital industries to design an approximate multiplier with low power and minimum error rate with higher *** overcome these issues,the digital circuits are applied to the Deep Learning(DL)approaches for higher *** recent times,DL is the method that is used for higher learning and prediction accuracy in severalﬁ***,the Long Short-Term mem.ry(LSTm)is a popular time series DL method is used in this work for approximate *** provide an optimal solution,the LSTm is combined with a meta-heuristics Jel-lyﬁsh search optimisation technique to design an input aware deep learning-based approximate multiplier(DLAm).In this work,the jelly optimised LSTm model is used to enhance the error metrics performance of the Approximate *** optimal hyperparameters of the LSTm model are identiﬁed by jelly search ***ﬁne-tuning is used to obtain an optimal solution to perform an LSTm with higher *** proposed pre-trained LSTm model is used to generate approximate design libraries for the different truncation levels as a func-tion of area,delay,power and error *** experimental results on an 8-bit multiplier with an image processing application shows that the proposed approx-imate computing multiplier achieved a superior area and power reduction with very good results on error rates.

关键词： Deep learning approximate multiplier LSTm jellyﬁsh

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modeling of organic pollutant destruction in a stirred tank reactor by ozonation

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Journal of environmental Sciences 2001年第4期13卷 449-452页

作者： CHeNG Jiang YANG Zhuo-ru CHeN Huan-qin KUO C.H. ZAPPI e.m. College of Chemical engineering South China University of TechnologyGuangzhou 510641China Swalm School of Chemical engineering Mississippi State UniversityMS 39762StarkvilleUSA

Destruction of organic contaminants in water by ozonation is a gas-liquid process which involves ozone mass transfer and fast irreversible chemical reactions. Ozonation reactor design and process optimizing require the modeling of the gas-liquid interactions within the reactor. In this paper a theoretical model combining the fluid dynamic and reaction kinetic parameters is proposed for predicting the destruction rates of organic pollutants in a semi-batch stirred-tank reactor by ozonation. A simple expression for the enhancement factor as our previous work has been applied to evaluate the chemical mass transfer coefficient in ozone absorption. 2,4-dichlorophenol (2,4-DCP) and 2,6-DCP or their mixture are chosen as the model compounds for simulating, and the predicted DCP concentrations are compared with some measured data.

关键词： dichlorophenol destruction ozonation stirred-tank reactor enhancement factor

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