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排序方式: 共有427条查询结果,搜索用时 15 毫秒
1.
Agrawal Yash Kumar Manoranjan Ananthakrishnan Supriya Kumarapuram Gopalakrishnan 《Water Resources Management》2022,36(3):1025-1042
Water Resources Management - The present study investigates and evaluate the scope and potential of modern computing tools and techniques such as ensembled machine learning methods in estimating... 相似文献
2.
Bahl L.R. de Souza P.V. Gopalakrishnan P.S. Kanevsky D.S. Nahamoo D. 《Signal Processing, IEEE Transactions on》1992,40(11):2814-2816
A method for identifying a set of candidate words that matches well with a given utterance is discussed. The method uses precomputed groups of acoustically similar words. Given a vocabulary, for each word a short list of words that are acoustically similar to it is computed. These groups are constructed using training utterances recorded by several speakers and used in an isolated utterance recognition system to construct candidate word lists during recognition. Experiments show that the correct word appears on the short list of candidate words constructed during recognition using this scheme over 98% of the time 相似文献
3.
4.
A neuro-fuzzy approach to automatic diagnosis and location of stator inter-turn faults in CSI-fed PM brushless DC motors 总被引:2,自引:0,他引:2
Awadallah M.A. Morcos M.M. Gopalakrishnan S. Nehl T.W. 《Energy Conversion, IEEE Transaction on》2005,20(2):253-259
The paper presents a neuro-fuzzy-based perspective to the automation of diagnosis and location of stator-winding interturn short circuits in CSI-fed brushless dc motors. Performance of the drive under normal and short-circuit conditions are obtained through classical lumped-parameter network models. Waveforms of the electromagnetic torque and summation of phase voltages are monitored to develop two independent diagnostic algorithms. Diagnostic indices derived from the characteristic waveforms using discrete Fourier transform (DFT) lead to identifying the number of shorted turns. Fault location is achieved through a different set of indices extracted by the short-time Fourier transform (STFT). Adaptive neuro-fuzzy inference systems (ANFIS) are trained based on simulation results to automate the diagnostic process. ANFIS testing along with the good agreement between simulated and measured waveforms show the effectiveness of the proposed techniques. 相似文献
5.
B. V. R. Chowdari R. Gopalakrishnan S. H. Goh K. L. Tan 《Journal of Materials Science》1988,23(4):1248-1254
Ionic conductivity of the Ag2O-MoO3-V205 system has been studied over a wide range of frequency, temperature and composition. A narrower glass forming region has been found in comparison to the corresponding Ag2O-MoO3-P2O5 and Ag2O-B2O3-P2O5 systems. The highest conductivity at room temperature, rt, = 3.21 × 10–6–1 cm–1 (d.c.) with an activation energy,E
act, of 0.466 eV, was observed for the glass former's ratio of unity. Further, it reached a maximum value of 2.2 × 10–2¨-1 cm–1 withE
act = 0.153 eV when the oxide-base glass was dissolved with Agl. D.c. conductivity, hopping rate and relaxation time in the present system have been found to be characterized by the same activation energy. 相似文献
6.
An Efficient Lossless Telemetry Data Compression and Fault Analysis System Using 2SMLZ and CMOW-DLNN
Ramalingam Parameshwaran Thanuja R. Bhavani R. Gopalakrishnan Lakshminarayanan 《Wireless Personal Communications》2022,122(3):2325-2334
Wireless Personal Communications - In this paper, the effect of perfect electric conductor (PEC) as a ground plane on antenna array is investigated. Vertical electric dipole which is of... 相似文献
7.
L. Ganapathi G. N. Subbanna J. Gopalakrishnan C. N. R. Rao 《Journal of Materials Science》1985,20(3):1105-1110
High resolution electron microscopic (HREM) investigation of potassium-alumina and the related gallate and ferrite has revealed that whereas the aluminate and gallate are highly disordered, consisting of random sequence of and units, the ferrite is more ordered. The aluminate and gallate are sensitive to electron beam irradiation exhibiting beam-induced damage similar to sodium-alumina. Significantly, the ferrite is beamstable, the difference in behaviour amongst these related oxides arising from the different mechanisms by which alkali metal nonstoichiometry is accommodated. Barium hexaaluminate and hexaferrite are both highly ordered; specimens prepared by the barium borate flux method exhibit a new 3a×3a superstructure of the hexagonal magnetoplumbite cell.Contribution No. 241 from the Solid State and Structural Chemistry Unit. 相似文献
8.
O. D. Jayakumar I. K. Gopalakrishnan S. K. Kulshreshtha 《Journal of Materials Science》2006,41(15):4706-4712
Fe- and Cu-doped ZnO of nominal compositions Zn0.95Fe0.05O and Zn0.94Fe0.05Cu0.01O were synthesized by a wet chemical route. X-ray diffraction analysis of the samples annealed at 575 K showed that they are single phase without any secondary phases. DC magnetization measurements of Cu co-doped samples (Zn0.94Fe0.05Cu0.01O) as a function of field at room temperature showed ferromagnetic signature while the samples without Cu co-doping (Zn0.95Fe0.05O) are paramagnetic in nature. On increasing the temperature of annealing from 575 K to 1,075 K an impurity phase emerges in both the samples, which has been identified as a variant of ZnFe2O4. Both the samples heated at and above 1,075 K are found to be paramagnetic at room temperature. These observations, the absence of room temperature ferromagnetism in Zn0.95Fe0.05O and the disappearance of ferromagnetism in Zn0.94Fe0.05Cu0.01O on raising the temperature of annealing clearly rules out the likelihood of room temperature ferromagnetism arising from the impurity phases like γ-Fe2O3 and/or ZnFe2O4 that might have been formed during the synthesis. Our results strongly suggest that room temperature ferromagnetism in Zn0.94Fe0.05Cu0.01O can be attributed to the formation of a secondary phase of Cu-doped ZnFe2O4. 相似文献
9.
A.K. Garg D. Roy Mahapatra S. Suresh S. Gopalakrishnan S.N. Omkar 《Composites Science and Technology》2004,64(16):2477-2493
A multi-layer perceptron (MLP) network using error back propagation algorithm is employed in this paper to estimate the damage parameters from broad-band spectral data as diagnostic signal. Various existing models of damage in laminated composite and the resulting stiffness degradation are discussed from comparative view-point. Degradation of ply properties can be considered to be one of the damage model parameters while monitoring transverse matrix cracks in cross-ply, splitting in longitudinal ply, and evolution of consecutive stages of damage, such as delaminations and fiber fracture. The stiffness degradation factor, the location and size of the damaged zone in laminated composite beam are considered as damage model parameters in the present paper. Fourier spectral data, which is typical to most of the diagnostic wave measurements, are used as input to the neural network. Since, training the neural network in such case involves many data sets and all of these data are difficult to generate using experiments, a spectral finite element model (SFEM) with embedded degraded zone in laminated composite beam is developed. Numerical simulation using this element is carried out, which shows the nature of temporal signal that are likely to be measured. Analytical studies on the performance of the neural network are presented based on numerically simulated data. Effect of measurement noise on the network performance is also reported. 相似文献
10.
This paper deals with the development of a neural computing system that can predict the cutting tool path length for milling an arbitrary pocket defined within the domain of a product design, in a computer numerically controlled (CNC) setting. Existing computer aided design and manufacturing systems (CAD/CAM) consume significant amounts of time in terms of data entry pertaining to the geometries and subsequent modifications to them. In the concurrent engineering environment, where even the designer needs information from the CAD/CAM systems, such time-consuming processes can be expensive. To alleviate this problem, a neural network system can be used to estimate machining time by predicting cost-dependent variables such as tool path length for the pocket milling operation. Pockets are characterized and classified into various groups. A randomized design is described so that the training samples that have been chosen represent the domain evenly. An appropriate network was built and trained with the sample pocket geometries. The analysis of the performance of the system in terms of tool path length prediction for new pocket geometries is presented. 相似文献