Relevant bibliographies by topics / Complex Transformer

Academic literature on the topic 'Complex Transformer'

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Published: 6 September 2023

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Journal articles on the topic "Complex Transformer"

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Ivanov, Georgi, Anelia Spasova, Valentin Mateev, and Iliana Marinova. "Applied Complex Diagnostics and Monitoring of Special Power Transformers." Energies 16, no. 5 (February 22, 2023): 2142. http://dx.doi.org/10.3390/en16052142.

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As a major component in electric power systems, power transformers are one of the most expensive and important pieces of electrical equipment. The trouble-free operation of power transformers is an important criterion for safety and stability in a power system. Technical diagnostics of electrical equipment are a mandatory part of preventing accidents and ensuring the continuity of the power supply. In this study, a complex diagnostic methodology was proposed and applied for special power transformers’ risk estimation. Twenty special power transformers were scored with the proposed risk estimation methodology. For each transformer, dissolved gas analysis (DGA) tests, transformer oil quality analysis, visual inspections of all current equipment on-site and historical data for the operation of each electrical research were conducted. All data were collected and analyzed under historical records of malfunctioning events. Statistical data for expected fault risk, based on long-term records, with such types of transformers were used to make more precise estimations of the current state of each machine and expected operational resource. The calculated degree of insulation polymerization was made via an ANN-assisted predictive method. Assessment of the collected data was applied to allow detailed information of the state of the power transformer to be rated. A method for risk assessment and reliability estimation was proposed and applied, based on the health index (HI) for each transformer.
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Fiennes, J., and C. R. de Souza. "The Complex Transformer as a Network-Model Element." International Journal of Electrical Engineering & Education 40, no. 1 (January 2003): 27–35. http://dx.doi.org/10.7227/ijeee.40.1.3.

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Jamali, Ali, and Masoud Mahdianpari. "Swin Transformer for Complex Coastal Wetland Classification Using the Integration of Sentinel-1 and Sentinel-2 Imagery." Water 14, no. 2 (January 10, 2022): 178. http://dx.doi.org/10.3390/w14020178.

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The emergence of deep learning techniques has revolutionized the use of machine learning algorithms to classify complicated environments, notably in remote sensing. Convolutional Neural Networks (CNNs) have shown considerable promise in classifying challenging high-dimensional remote sensing data, particularly in the classification of wetlands. State-of-the-art Natural Language Processing (NLP) algorithms, on the other hand, are transformers. Despite the fact that transformers have been utilized for a few remote sensing applications, they have not been compared to other well-known CNN networks in complex wetland classification. As such, for the classification of complex coastal wetlands in the study area of Saint John city, located in New Brunswick, Canada, we modified and employed the Swin Transformer algorithm. Moreover, the developed transformer classifier results were compared with two well-known deep CNNs of AlexNet and VGG-16. In terms of average accuracy, the proposed Swin Transformer algorithm outperformed the AlexNet and VGG-16 techniques by 14.3% and 44.28%, respectively. The proposed Swin Transformer classifier obtained F-1 scores of 0.65, 0.71, 0.73, 0.78, 0.82, 0.84, and 0.84 for the recognition of coastal marsh, shrub, bog, fen, aquatic bed, forested wetland, and freshwater marsh, respectively. The results achieved in this study suggest the high capability of transformers over very deep CNN networks for the classification of complex landscapes in remote sensing.
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Sun, Yuanyuan, Gongde Xu, Na Li, Kejun Li, Yongliang Liang, Hui Zhong, Lina Zhang, and Ping Liu. "Hotspot Temperature Prediction of Dry-Type Transformers Based on Particle Filter Optimization with Support Vector Regression." Symmetry 13, no. 8 (July 22, 2021): 1320. http://dx.doi.org/10.3390/sym13081320.

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Both poor cooling methods and complex heat dissipation lead to prominent asymmetry in transformer temperature distribution. Both the operating life and load capacity of a power transformer are closely related to the winding hotspot temperature. Realizing accurate prediction of the hotspot temperature of transformer windings is the key to effectively preventing thermal faults in transformers, thus ensuring the reliable operation of transformers and accurately predicting transformer operating lifetimes. In this paper, a hot spot temperature prediction method is proposed based on the transformer operating parameters through the particle filter optimization support vector regression model. Based on the monitored transformer temperature, load rate, transformer cooling type, and ambient temperature, the hotspot temperature of a dry-type transformer can be predicted by a support vector regression method. The hyperparameters of the support vector regression are dynamically optimized here according to the particle filter to improve the optimization accuracy. The validity and accuracy of the proposed method are verified by comparing the proposed method with a traditional support vector regression method based on the real operating data of a 35 kV dry-type transformer.
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Xu, Honghua, Yong Li, Lei Zhu, and Ziqiang Xu. "Condition assessment of transformers in wind farm based on modified one-dim residual neural network." Journal of Physics: Conference Series 2378, no. 1 (December 1, 2022): 012078. http://dx.doi.org/10.1088/1742-6596/2378/1/012078.

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Abstract The working environment of transformers in the wind farm is more complex than others, which brings the difference in condition assessment. Moreover, many condition assessment methods based on characteristics or machine learning have difficulty in recognition in cases of multiple transformers, conditions and measuring points. To assess conditions, this paper establishes a condition classification model of the transformer with a modified one-dim residual neural network and uses vibration signal, current and voltage as inputs. The built network mode has faster convergence speed and classification accuracy in transformer condition assessment and is more suitable for transformer condition assessment than the original one.
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Andjelic, Zoran, Ramsis Girgis, Asim Fazlagic, Alessandro Regalino, Claude J. Lambert, A. Seidel, and M. Ries. "Structural-mechanics analysis of the 10g transformer impact." Journal of Energy - Energija 63, no. 1-4 (July 2, 2022): 104–13. http://dx.doi.org/10.37798/2014631-4168.

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Transportation of the power transformers from the site of production to the site of the exploitation is very complex and sensible task. During transportation, the transformer can be subjected to a variety of different impacts registered either during railway transportation or during on/off loading. The transformer should be designed to sustain the high accelerations appearing often during transportation. Transformer are usually equipped with the impact recorder to registry the acceleration behavior during the transport. In the current paper, we give an overview on the structural-mechanics analysis of 10g impact on the power transformer registered during the railway transportation of the transformer from Canada to US.
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Azmi Murad Abd Aziz, Mohd Aizam Talib, Ahmad Farid Abidin, and Syed Abdul Mutalib Al Junid. "Development of Power Transformer Health Index Assessment Using Feedforward Neural Network." Journal of Advanced Research in Applied Sciences and Engineering Technology 30, no. 3 (May 15, 2023): 276–89. http://dx.doi.org/10.37934/araset.30.3.276289.

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The role of a power transformer is to convert the electrical power level and send it to the consumer, making it an essential component of a power system. In addition, transformer asset management is essential for monitoring the functioning of transformers in the system to prevent failure and anticipating the health state of transformers, using a technique known as the health index (HI). However, the calculation and computation to determine the transformer HI based on a scoring and ranking technique is complex and required expert validation. Therefore, this paper presents a transformer HI prediction using a feedforward neural network (FFNN) to improve the existing complex scoring and ranking technique. Levenberg–Marquardt (LM), Bayesian Regularized (BR), and Scaled Conjugate Gradient (SCG) are the FFNN training techniques presented in this study to forecast the transformer HI. To validate the techniques, the HI values generated by different FFNN techniques were compared to the scoring and ranking system. Then, the performance of the proposed ANN was evaluated using the correlation coefficient and mean square error (MSE). As a result, the transformer HI was successfully predicted by employing three FFNN techniques, namely the LM, BR, and SCG techniques, which were able to determine whether the transformer's condition is very good, good, fair, or poor. In conclusion, the ANN suggested in this study has also been validated with the ranking and scoring approach, which provides high similarity score in comparison to the transformer health index.
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Stosic, Biljana. "Wave digital models of ideal and real transformers." Facta universitatis - series: Electronics and Energetics 29, no. 2 (2016): 219–31. http://dx.doi.org/10.2298/fuee1602219s.

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In this paper, the wave digital filter (WDF) theory is applied for development of the wave digital models of ideal and real transformers which can be used for modeling of more complex structures. The transformers wave digital networks are described and developed here based on scattering variables and two-port and three-port networks of parallel and series adaptors. WDF-based model of a real transformer includes parasitic resistors and inductors, which are usual in low-frequency transformer equivalent circuit.
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Lin, Yuyin, Yuzi Lin, Qingyu Wu, Xinhai Wu, Jiayi Tu, Weisheng Ren, Yu Lu, Yaoyin Zhang, Engang Cheng, and Xiangyu Guan. "Anti-interference detection and operation state identification of transformer acoustic characteristics based on Conv-Tas-ResNet." Journal of Physics: Conference Series 2399, no. 1 (December 1, 2022): 012039. http://dx.doi.org/10.1088/1742-6596/2399/1/012039.

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Abstract There is a limitation in the process of acoustic signal detection, which lies in serious background noise interference and the complex correlation between acoustic signal characteristics and operation states. Integrating the denoising model and feature classification model, a method of transformer acoustic signal anti-interference detection and operation state detection based on deep learning is proposed in this paper. Through tests in anechoic rooms, acoustic signals of transformers in the normal state or under harmonic load are acquired. Combining these signals with the background noise, a dataset containing 12000 samples of acoustic signals is constructed. To implement anti-interference detection, Conv-TasNet is utilized to get the transformer acoustic signal and environmental noise separated; then, ResNet is utilized to classify the operation states of the transformer accurately. Results show that compared with the blind source separation method through RNN and FastICA, the denoising model established in this paper improves Si-SDRi parameters by 37.4dB and 17.53dB respectively, and the transformer operation state classification model established in this paper classifies the test dataset with an accuracy of 97.7%, thus providing an effective method for the extraction of transformer acoustic signal and diagnosis of transformer operation states in complex environments.
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Li, Zhi Bin, and Qi Ben Li. "Multi-Level Fault Diagnosis of Power Transformer Based on Fusion Technology." Advanced Materials Research 860-863 (December 2013): 1925–28. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.1925.

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Traditional transformer fault diagnosis based on single source of information has significant limitation in identification of transformer fault type because of power transformers complex structure and changeable operating environment. So fusion technology is introduced into the fault diagnosis of power transformer. This method divides the progress of transformer fault diagnosis into two fusion levels. The first level is to ascertain whether it is overheated or discharged by content of gases dissolved in transformer oil. The second level is to ascertain the location or cause of the fault by electric data. The intelligence algorithms which are used in these two levels are both the improved BP neural network algorithm. Finally, the effectiveness is validated by the result of practical fault diagnosis examples.
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Dissertations / Theses on the topic "Complex Transformer"

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Tavakoli, Hanif. "A High Frequency Transformer Winding Model for FRA Applications." Licentiate thesis, Stockholm : Skolan för elektro- och systemteknik, Kungliga Tekniska högskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-11178.

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Tavakoli, Hanif. "An FRA Transformer Model with Application on Time Domain Reflectometry." Doctoral thesis, KTH, Elektroteknisk teori och konstruktion, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-48568.

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Frequency response analysis (FRA) is a frequency-domain method which is used to detect mechanical faults in transformers. The frequency response of a transformer is determined by its geometry and material properties, and it can be considered as the transformer’s fingerprint. If there are any mechanical changes in the transformer, for example if the windings are moved or distorted, its fingerprint will also be changed so, theoretically, mechanical changes in the transformer can be detected with FRA. A problem with FRA is the fact that there is no general agreement about how to interpret the measurement results for detection of winding damages. For instance, the interpretation of measurement results has still not been standardized.The overall goal of this thesis is to try to enhance the understanding of the information contained in FRA measurements. This has been done in two ways: (1) by examining the FRA method for (much) higher frequencies than what is usual, and (2) by developing a new method in which FRA is combined with the ideas of Time Domain Reflectometry (TDR). As tools for carrying out the above mentioned steps, models for the magnetic core and the winding have been developed and verified by comparison to measurements.The usual upper frequency limit for FRA is around 2 MHz, which in this thesis has been extended by an order of magnitude in order to detect and interpret new phenomena that emerge at high frequencies and to investigate the potential of this high-frequency region for detection of winding deteriorations.Further, in the above-mentioned new method developed in this thesis, FRA and TDR are combined as a step towards an easier and more intuitive detection and localization of faults in transformer windings, where frequency response measurements are visualized in the time domain in order to facilitate their interpretation.
QC 20111122
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Завадський, Богдан Володимирович, and Bohdan Zavadskyi. "Оптимізація системи електропостачання трансформаторної підстанції 110/10 кВ." Master's thesis, Тернопільський національний технічний університет імені Івана Пулюя, кафедра електричної інженерії,Тернопіль, Україна, 2021. http://elartu.tntu.edu.ua/handle/lib/36648.

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У зв'язку зі зростанням технологічного прогресу, розумні системи все частіше використовуються в різних сферах людської діяльності. Розумні системи дозволяють технікам, адміністраторам і менеджерам контролювати і продуктивність і роботу пристроїв з безпечної відстані. Сфера енергетики не є винятком. Розподільчі мережі компанії повинні управляти розподільною мережею, яка є однією з найважливіших частин електромережі [1]. В даний час для загального розвитку промисловості країни необхідні трансформації в енергетичному секторі. Завдання цифровізації енергетики було поставлено на найвищому рівні[2]. Традиційно пропускна здатність мережі визначається на основі пікового використання. Таке використання може відображати споживання енергії лише протягом декількох годин на рік; Наприклад, пізно вночі посеред зими. Дорогих мережевих посилень в майбутньому можна уникнути, якщо ці піки енергоспоживання можуть бути компенсовані. Це починає відбуватися в міру того, як структура виробництва енергії змінюється і стає все більш залежною від поновлюваних джерел енергії, а не від традиційних електростанцій. Крім того, домогосподарства мають потенціал стати автономними, збільшуючи доступність внутрішнього зберігання та виробництва енергії [3]. Розумні лічильники повідомлять енергопостачальну організацію про збої передачі електроенергії, що допоможе поліпшити обслуговування клієнтів. Замість того, щоб чекати, поки перший споживач повідомить про це, мережеві організації зможуть реагувати, як тільки буде отримано перше попередження про відмову розумного лічильника. Розумні лічильники також повідомлять суб'єктів ринку електроенергії, якщо якість електропостачання, наприклад, рівень напруги, виходить за межі заданих рівнів. Це допоможе енергосистемам краще зрозуміти якість їх поставок і усунути недоліки [4].
У кваліфікаційній роботі магістра здійснено розробку технічних заходів щодо оптимізації системи електропостачання мережі трансформаторної підстанції 110/10 кВ. Встановлено, що необхідно забезпечити мережу ПС 110/10 кВ засобами дистанційного моніторингу параметрів на усіх рівнях. Отримані дані для місць розташування засобів контролю. Визначені чинники, що впливають на зниження ефективності процесу передачі електроенергії електричною мережею. Проведено дослідження моніторингу параметрів трансформатора засобами установки вимірювальних комплексів як з боку високої напруги так і з боку низької напруги. За виміряними даними побудований графік втрат в трансформаторі. Розроблені алгоритми на основі даних моніторингу і їх застосування на практиці для підвищення ефективності передачі електроенергії мережею.
In qualifying work of master's degree development of technical measures is carried out it is Set in relation to optimization of the system of power supply of network of transformer substation of 110/10 кВ., that it is necessary to provide a network by 110/10 кВ facilities of RMON of parameters on all levels. The locations of controls given for places are got. Certain factors that influence on the decline of efficiency of process of transmission of electric power an electric network. Research of monitoring of parameters of transformer is conducted by facilities of setting of measuring complexes as from the side of high tension so from the side of low tension. From measured data the built chart of losses is in a transformer. Worked out algorithms on the basis of data of monitoring and their application in practice for the increase of efficiency of transmission of electric power by a network.
ЗМІСТ ВСТУП 6 1 АНАЛІТИЧНИЙ РОЗДІЛ 9 1.1 Аналіз високовольтної мережі підстанції 110/10 кВ 9 1.2 Аналіз мережі середньої напруги ПС 110/10 кВ 12 1.3 Аналіз мережі низької напруги ПС 110/10 кВ 16 1.4 Висновки до розділу 1 17 2 РОЗРАХУНКОВО-ДОСЛІДНИЦЬКИЙ РОЗДІЛ 18 2.1 Існуючі методи контролю параметрів мережі 18 2.2 Критичний аналіз існуючих методів контролю параметрів мережі 21 2.3 Контроль втрат в мережі 110/10/0,4 кВ 24 2.4 Контроль величини втрат в трансформаторі і лінії 36 2.5 Висновки до розділу 2 39 3 ПРОЕКТНО-КОНСТРУКТОРСЬКИЙ РОЗДІЛ 40 3.1 Застосування розрахунку втрат по методу оперативних даних 40 3.2 Компенсація реактивної потужності 43 3.3 Інтелектуальна система АЧР 46 3.4 Використання моніторингу при технологічному приєднанні 48 3.5 Алгоритм визначення нетехнічних втрат 51 3.6 Нерівномірне навантаження в мережах 220-380 В 60 3.7 Контроль показників якості електроенергії 60 3.8 Контроль температури приладів обліку 61 3.9 Висновки до розділу 3 62 5 4 ОХОРОНА ПРАЦІ ТА БЕЗПЕКА В НАДЗВИЧАЙНИХ СИТУАЦІЯХ 63 4.1 Безпека праці електромонтера по обслуговуванню трансформаторних підстанцій і розподільних пунктів 63 4.2 Принципи і заходи підвищення стійкості функціонування об'єктів економіки 67 ЗАГАЛЬНІ ВИСНОВКИ 70 ПЕРЕЛІК ПОСИЛАНЬ 72
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Sari, Huseyin. "Motion Estimation Using Complex Discrete Wavelet Transform." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1223205/index.pdf.

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The estimation of optical flow has become a vital research field in image sequence analysis especially in past two decades, which found applications in many fields such as stereo optics, video compression, robotics and computer vision. In this thesis, the complex wavelet based algorithm for the estimation of optical flow developed by Magarey and Kingsbury is implemented and investigated. The algorithm is based on a complex version of the discrete wavelet transform (CDWT), which analyzes an image through blocks of filtering with a set of Gabor-like kernels with different scales and orientations. The output is a hierarchy of scaled and subsampled orientation-tuned subimages. The motion estimation algorithm is based on the relationship between translations in image domain and phase shifts in CDWT domain, which is satisfied by the shiftability and interpolability property of CDWT. Optical flow is estimated by using this relationship at each scale, in a coarse-to-fine (hierarchical) manner, where information from finer scales is used to refine the estimates from coarser scales. The performance of the motion estimation algorithm is investigated with various image sequences as input and the effects of the options in the algorithm like curvature-correction, interpolation kernel between levels and some parameter values like confidence threshold iv maximum number of CDWT levels and minimum finest level of detail are also experimented and discussed. The test results show that the method is superior to other well-known algorithms in estimation accuracy, especially under high illuminance variations and additive noise.
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Yilmaz, Sener. "Generalized Area Tracking Using Complex Discrete Wavelet Transform: The Complex Wavelet Tracker." Phd thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/3/12608643/index.pdf.

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In this work, a new method is proposed that can be used for area tracking. This method is based on the Complex Discrete Wavelet Transform (CDWT) developed by Magarey and Kingsbury. The CDWT has its advantages over the traditional Discrete Wavelet Transform such as approximate shift invariance, improved directional selectivity, and robustness to noise and illumination changes. The proposed method is a generalization of the CDWT based motion estimation method developed by Magarey and Kingsbury. The Complex Wavelet Tracker extends the original method to estimate the true motion of regions according to a parametric motion model. In this way, rotation, scaling, and shear type of motions can be handled in addition to pure translation. Simulations have been performed on the proposed method including both quantitative and qualitative tests. Quantitative tests are performed on synthetically created test sequences and results have been compared to true data. The performance is compared with intensity-based methods. Qualitative tests are performed on real sequences and evaluations are presented empirically. The results are compared with intensity-based methods. It is observed that the proposed method is very accurate in handling affine deformations for long term sequences and is robust to different target signatures and illumination changes. The accuracy of the proposed method is compatible with intensity-based methods. In addition to this, it can handle a wider range of cases and is robust to illuminaton changes compared to intensity-based methods. The method can be implemented in real-time and could be a powerful replacement of current area trackers.
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Ferreira, Rafael Fransak. "Filogenia do Complexo Drosophila Buzzatii (Grupo Repleta): Inferências de Análises Multilocus Mitocondriais e Nucleares." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/17/17135/tde-26092011-154314/.

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O complexo Drosophila buzzatii (grupo repleta) compreende 13 espécies, divididas em três clusters, de acordo com o bandeamento observado nos cromossomos politênicos: cluster D. stalkeri, incluindo D. richardsoni e D. stalkeri, restrito às ilhas do Caribe e Flórida; cluster D. martensis, incluindo D. martensis, D. uniseta, D. venezolana e D. starmeri, encontrado em áreas desérticas da Colômbia e Venezuela; e cluster D. buzzatii, incluindo D. buzzatii, D. koepferae, D. antonietae, D. serido, D. gouveai, D. borborema e D. seriema, habitando regiões sazonalmente secas ao longo da diagonal de vegetação aberta da América do Sul. O presente estudo teve como objetivo inferir as relações filogenéticas entre as espécies do complexo D. buzzatii, dando ênfase ao cluster D. buzzatii, por meio de análises multilocus de genes mitocondriais (COI e COII) e nucleares (EF-1F1, transformer e period). Nas hipóteses filogenéticas estabelecidas, as espécies do complexo D. buzzatii constituíram um grupo monofilético, composto por dois subgrupos monofiléticos, os clusters D. martensis e D. buzzatii, e um parafilético, o cluster D. stalkeri. As relações de parentesco entre as espécies do cluster D. buzzatii foram estabelecidas. Drosophila buzzatii ocupou a posição mais basal dentro do cluster D. buzzatii, estando proximamente relacionada à espécie D. koepferae. Drosophila antonietae ocupou uma posição intermediária em relação às espécies D. koepferae e D. serido, que representa o táxon irmão do ramo formado por D. gouveai, D. borborema e D. seriema, com D. gouveai ocupando uma posição mais basal em relação às espécies irmãs D. borborema e D. seriema. Foi detectada seleção purificadora como a principal força dirigindo a evolução dos genes nucleares transformer e period, para as espécies do complexo D. buzzatii. O gene mitocondrial COI, por sua vez, foi utilizado para estimar os tempos de divergência para as espécies do cluster D. buzzatii, revelando que o processo de diversificação do grupo iniciou-se no período Plioceno, provavelmente em decorrência de eventos de vicariância associados à elevação dos Andes, sendo também influenciado pelo avanço e retração da vegetação xerófita, nas flutuações climáticas do Pleistoceno.
Drosophila buzzatii complex (repleta group) consists of 13 species, divided into three clusters according to the banding seen in polytene chromosomes: D. stalkeri cluster, including D. richardsoni and D. stalkeri, restricted to the Caribbean Islands and Florida; D. martensis cluster, including D. martensis, D. uniseta, D. venezuelana and D. starmeri, found in desert areas of Colombia and Venezuela, and D. buzzatii cluster, including D. buzzatii, D. koepferae, D. antonietae, D.gouveai, D. borborema and D. seriema, that inhabit seasonally dry regions along the open vegetation diagonal in South America. This study aimed to infer the phylogenetic relationships among the D. buzzatii species complex, emphasizing the D. buzzatii cluster, by multilocus analysis of mitochondrial (COI and COII) and nuclear (EF-1F1, transformer and period) genes. In established phylogenetic hypotheises, the species of the D. buzzatii complex formed a monophyletic group, composed of two monophyletic subgroups, the D. martensis and D. buzzatii clusters, and a paraphyletic one, the D. stalkeri cluster. The relationships among the D. buzzatii species cluster were established. Drosophila buzzatii occupied the most basal position within the D. buzzatii cluster and is closely related to D. koepferae. D. antonietae occupied an intermediate position in relation to the D. koepferae and D. serido species. D. serido represents the sister taxon of the branch formed by the D. gouveai, D. borborema and D. seriema species, with D. gouveai occupying a basal position in relation to the sister species D. borborema and D. seriema. It was detected that purifying selection is the main force driving the evolution of transformer and period nuclear genes for the species of the D. buzzatii complex. The divergence time of the D. buzzatii species cluster was estimated by the COI gene analysis, revealing that the process of diversification of the group began in the Pliocene period, probably due to vicariant events associated with the uplift phase of the Andes, and it was also influenced by the advance and retraction of xerophytic vegetation in Pleistocene climatic fluctuations.
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Daza, Enrique Acha. "Modelling of power system transformers in the complex conjugate harmonic space." Thesis, University of Canterbury. Electrical Engineering, 1988. http://hdl.handle.net/10092/5450.

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Magnetizing harmonics in power systems have received limited attention. The general belief is that they do not reach harmful levels in interconnected networks. Moreover the modelling of non-linearities is not a straightforward procedure and so there has been little motivation to develop appropriate methodologies that allow a thorough investigation to take place. In this thesis the problem of magnetizing harmonics in power systems is investigated. The results obtained show that, contrary to expectations, magnetizing currents can give rise to a considerable harmonic distortion in the voltage wave form of power networks operating under loaded conditions. The method adopted in this research linearizes each magnetic non-linearity around a base operating point. The linearization exercise takes place in the complex-conjugate harmonic space and the individual linearized equations may be interpreted as harmonic Norton equivalents. These equations combine easily with each other and with the transfer admittances representing the linear part of the network. The overall process of linearization may be seen as a linearization of the entire network and can also be interpreted as a multi-nodal, polyphase harmonic Norton equivalent. This problem is non-linear and the harmonic solution is reached by an iterative process. A re-linearization of the network takes place at each iterative step and so the solution is found through a Newton-type procedure. Several iterative strategies are tested, including unified and sequential solutions with either single or multi-evaluated Jacobians. A hitherto neglected problem which also receives attention is the harmonic modelling of non-homogenous transmission lines. A novel approach to the modelling of the frequency dependent part of the transmission line is also presented. The equations proposed are shown to be the fastest to date and yet maintain a high degree of accuracy.
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Casseli, Irène. "Eléments sur la transformée de Berezin et sur les opérateurs de Toeplitz dans des espaces de fonctions polyanalytiques." Thesis, Aix-Marseille, 2019. http://www.theses.fr/2019AIXM0578.

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Les fonctions polyanalytiques entières généralisent les fonctions entières dans la mesure où elles sont les solutions sur le plan complexe \mathbb{C} de l'équation de Cauchy-Riemann à l'ordre n, de la forme { partial} nf / \partial \overline{z} n = 0. Un espace de Fock polyanalytique F2 {\alpha,n} est, par analogie avec le cas classique, le sous-espace fermé de l'espace de Hilbert L^2 (\mathbb{C},d\mu \alpha), où \mu \alpha est une mesure de probabilité gaussienne sur \mathbb{C} de paramètre alpha>0, formé des fonctions polyanalytiques entières d'ordre n. L'objet de cette thèses est l'étude d'éléments classiques de la théorie des opérateurs tels que la transformée de Berezin et les opérateurs de Toeplitz dans le cadre particulier des espaces de Fock polyanalytiques. Dans ce manuscrit, il est montré en particulier que les points fixes de la transformée de Berezin qui appartiennent aux espaces de Lebesgue sont les fonctions nulles ou éventuellement constantes. Concernant les opérateurs de Toeplitz, le problème de Sarason est étudié. Etant donné une fonction f, l'opérateur de Toeplitz de symbole f est formellement défini par T {alpha,n} f(h)=P {alpha,n}(f h), où P {alpha,n} est la projection orthogonale de L^2(\mathbb{C},d\mu {alpha}) sur F^2 {alpha,n}. Le problème de Sarason consiste à donner une condition nécessaire et suffisante sur f et g pour que le produit d'opérateurs de symboles f et bar g soit continu
Entire polyanalytic functions generalize entire functions in that they are solutions of "Cauchy-Riemann equations of order n, of the form {\partial}^n f / \partial \overline{z}^n = 0, over the whole complex plane \mathbb{C}. Polyanalytic Fock space F^2_{\alpha,n} is, by analogy with the classical case, the closed subspace of the Hilbert space L^2(\mathbb{C},d\mu_\alpha), where \mu_\alpha is a Gaussian probability measure over \mathbb{C} with weight \alpha>0, of polyentire functions of order n. The aim of this PhD thesis is the study of classical objects of operator theory such that the Berezin transform and Toeplitz operators in the particular case of polyanalytic Fock spaces. In this written, it is shown among other results, that the L^p fixed points of the Berezin transform are constant functions. Concerning Toeplitz operators, the Sarason problem is studied. Given a function f, the Toeplitz operator with symbol f is formally defined by T^n_f(h)=P_{F^2_n}(f h), where P_{F^2_n} is the orthogonal projection from L^2(\mathbb{C},d\mu) on to F^2_n. The so-called Sarason's problem consists in finding necessary and sufficient conditions on the symbols f and g for the Toeplitz product with symbols f and \bar g to be bounded in the Fock space
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Thornton, A. L. "Colour object recognition using a complex colour representation and the frequency domain." Thesis, University of Reading, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301911.

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Reeves, Tanya Heather. "Overcomplete image coding using the dual-tree complex wavelet transform." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615767.

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Books on the topic "Complex Transformer"

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Kalluri, Dikshitulu K. Electromagnetics of time varying complex media: Frequency and polarization transformer. 2nd ed. Boca Raton, FL: CRC Press, 2010.

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Electromagnetics of time varying complex media: Frequency and polarization transformer. 2nd ed. Boca Raton: Taylor & Francis, 2010.

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Lanckau, Eberhard. Complex integral operators in mathematical physics. Leipzig: Barth, 1993.

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Bernd, Kirstein, and SpringerLink (Online service), eds. Interpolation, Schur Functions and Moment Problems II. Basel: Springer Basel, 2012.

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Simon, Barry. Basic complex analysis. Providence, Rhode Island: American Mathematical Society, 2015.

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1946-, Matheson Alec L., and Ross William T. 1964-, eds. The Cauchy transform. Providence, R.I: American Mathematical Society, 2006.

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Alpay, Daniel. Reproducing Kernel Spaces and Applications. Basel: Birkhäuser Basel, 2003.

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Maergoiz, L. S. Asymptotic Characteristics of Entire Functions and Their Applications in Mathematics and Biophysics. Dordrecht: Springer Netherlands, 2003.

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Bell, Steven Robert. The Cauchy transform, potential theory, and conformal mapping. Boca Raton, Fl: CRC Press, 1992.

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Fu bian han shu yu ji fen bian huan. 4th ed. Beijing: Gao deng jiao yu chu ban she, 2013.

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Book chapters on the topic "Complex Transformer"

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Nguyen, Nam Quan, Anh Duy Le, Anh Khoa Lu, Xuan Toan Mai, and Tuan Anh Tran. "Formerge: Recover Spanning Cells in Complex Table Structure Using Transformer Network." In Lecture Notes in Computer Science, 522–34. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-41734-4_32.

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Cai, Hua, Qing Xu, and Weilin Shen. "Complex Relative Position Encoding for Improving Joint Extraction of Entities and Relations." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 644–55. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_66.

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AbstractRelative position encoding (RPE) is important for transformer based pretrained language model to capture sequence ordering of input tokens. Transformer based model can detect entity pairs along with their relation for joint extraction of entities and relations. However, prior works suffer from the redundant entity pairs, or ignore the important inner structure in the process of extracting entities and relations. To address these limitations, in this paper, we first use BERT with complex relative position encoding (cRPE) to encode the input text information, then decompose the joint extraction task into two interrelated subtasks, namely head entity extraction and tail entity relation extraction. Owing to the excellent feature representation and reasonable decomposition strategy, our model can fully capture the semantic interdependence between different steps, as well as reduce noise from irrelevant entity pairs. Experimental results show that the F1 score of our method outperforms previous baseline work, achieving a better result on NYT-multi dataset with F1 score of 0.935.
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Smara, Anis, M. ’hana Bouktit, and Ahmed Boubakeur. "Swarm Intelligence Metaheurisics Application in the Diagnosis of Transformer Oil." In Proceedings of the Ninth International Conference on Dependability and Complex Systems DepCoS-RELCOMEX. June 30 – July 4, 2014, Brunów, Poland, 413–22. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07013-1_40.

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Chen, Bangdong, Dezhi Peng, Jiaxin Zhang, Yujin Ren, and Lianwen Jin. "Complex Table Structure Recognition in the Wild Using Transformer and Identity Matrix-Based Augmentation." In Frontiers in Handwriting Recognition, 545–61. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-21648-0_37.

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Basenko, Vasily, Oleg Vladimirov, Igor Ivshin, Marat Nizamiev, and Ilnur Usmanov. "Laser Control and Measuring Complex for Non-contact Vibration Control of the Power Transformer Technical Condition." In Lecture Notes in Civil Engineering, 157–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86047-9_17.

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Krantz, Steven G. "Other Transforms." In Complex Variables, 273–81. Second edition. | Boca Raton : CRC Press, Taylor & Francis Group, 2019.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9780429275166-15.

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Gordon, Ron. "Integral Transforms." In Complex Integration, 137–204. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-24228-1_5.

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Murthy, Garimella Rama, and Tapio Saramaki. "Complex Transforms." In Mining Intelligence and Knowledge Exploration, 382–91. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26832-3_36.

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Schiff, Joel L. "Complex Variable Theory." In The Laplace Transform, 115–50. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-0-387-22757-3_3.

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Schiff, Joel L. "Complex Inversion Formula." In The Laplace Transform, 151–74. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-0-387-22757-3_4.

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Conference papers on the topic "Complex Transformer"

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Yang, Muqiao, Martin Q. Ma, Dongyu Li, Yao-Hung Hubert Tsai, and Ruslan Salakhutdinov. "Complex Transformer: A Framework for Modeling Complex-Valued Sequence." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9054008.

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Yang, Gang, and Hongzhe Xu. "Complex-Valued Relative Positional Encodings for Transformer." In 2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE). IEEE, 2023. http://dx.doi.org/10.1109/nnice58320.2023.10105716.

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Saeed, Warda, Nosherwan Shoaib, Hammad M. Cheema, Muhammad U. Khan, and Fatima Khalid. "Triband Impedance Transformer for Frequency Dependent Complex Load." In 2018 18th International Symposium on Antenna Technology and Applied Electromagnetics (ANTEM). IEEE, 2018. http://dx.doi.org/10.1109/antem.2018.8572949.

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Liu, Yingqi, Guangyu Shen, Guanhong Tao, Shengwei An, Shiqing Ma, and Xiangyu Zhang. "Piccolo: Exposing Complex Backdoors in NLP Transformer Models." In 2022 IEEE Symposium on Security and Privacy (SP). IEEE, 2022. http://dx.doi.org/10.1109/sp46214.2022.9833579.

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Guo, Hongji, Hanjing Wang, and Qiang Ji. "Uncertainty-Guided Probabilistic Transformer for Complex Action Recognition." In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2022. http://dx.doi.org/10.1109/cvpr52688.2022.01942.

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Li, Qi, Tingjia Zhang, Yu Song, and Meiqi Sun. "Transformer-based spatial-temporal feature learning for P300." In 2022 16th ICME International Conference on Complex Medical Engineering (CME). IEEE, 2022. http://dx.doi.org/10.1109/cme55444.2022.10063297.

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Kang, Kaihang, Chuang Zhang, and Chen Guo. "Ship trajectory prediction based on transformer model." In 2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS). IEEE, 2022. http://dx.doi.org/10.1109/docs55193.2022.9967723.

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Cao, Qun, Xuchun Zhao, and Xiuzhen Li. "Study on the Energy Transmission of Simple Shape Amplitude Transformer." In 2007 IEEE/ICME International Conference on Complex Medical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/iccme.2007.4381706.

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Kriengket, Kanyanut, Kanchana Saengthongpattana, Peerachet Porkaew, Vorapon Luantangsrisuk, Prachya Boonkwan, and Thepchai Supnithi. "Behavioral Analysis of Transformer Models on Complex Grammatical Structures." In 2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). IEEE, 2020. http://dx.doi.org/10.1109/isai-nlp51646.2020.9376782.

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Guo, Yongquan, Hongmei Liu, Bin Luo, and Zhongbao Wang. "Modification of Susceptance Component Loaded Coupled Line Complex Impedance Transformer." In 2020 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC). IEEE, 2020. http://dx.doi.org/10.1109/csrswtc50769.2020.9372474.

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Reports on the topic "Complex Transformer"

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Krawchuk, Fred. Multi-Stakeholder Collaboration: How Government, Business, and Non-Governmental Leaders Transform Complex Challenges into New Possibilities. One Earth Future Foundation, November 2013. http://dx.doi.org/10.18289/oef.2013.001.

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Nuttall, Albert H. Two-Dimensional Convolutions, Correlations, and Fourier Transforms of Combinations of Wigner Distribution Functions and Complex Ambiguity Functions. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada226852.

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Hovakimyan, Naira, Hunmin Kim, Wenbin Wan, and Chuyuan Tao. Safe Operation of Connected Vehicles in Complex and Unforeseen Environments. Illinois Center for Transportation, August 2022. http://dx.doi.org/10.36501/0197-9191/22-016.

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Autonomous vehicles (AVs) have a great potential to transform the way we live and work, significantly reducing traffic accidents and harmful emissions on the one hand and enhancing travel efficiency and fuel economy on the other. Nevertheless, the safe and efficient control of AVs is still challenging because AVs operate in dynamic environments with unforeseen challenges. This project aimed to advance the state-of-the-art by designing a proactive/reactive adaptation and learning architecture for connected vehicles, unifying techniques in spatiotemporal data fusion, machine learning, and robust adaptive control. By leveraging data shared over a cloud network available to all entities, vehicles proactively adapted to new environments on the proactive level, thus coping with large-scale environmental changes. On the reactive level, control-barrier-function-based robust adaptive control with machine learning improved the performance around nominal models, providing performance and control certificates. The proposed research shaped a robust foundation for autonomous driving on cloud-connected highways of the future.
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Lutz, Carsten. Reasoning about Entity Relationship Diagrams with Complex Attribute Dependencies. Aachen University of Technology, 2002. http://dx.doi.org/10.25368/2022.119.

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Entity Relationship (ER) diagrams are among the most popular formalisms for the support of database design [7, 12, 17, 6]. Their classical use in the (usually computer aided) database design process can roughly be described as follows: after evaluating the requirements of the application, the database designer constructs an ER schema, which represents the conceptual model of the new database. CASE tools can be used to automatically transform the ER schema into a relational database schema, which is then manually fine-tuned. During the last years, the initially rather simple ER formalisms has been extended by various means of expressivity to account for new, more complex application areas such as schema integration for data warehouses [12, 3, 13]. Designing a conceptual model with such enriched ER diagrams is a nontrivial task: there exist complex interactions between the various means of expressivity, which quite often result in unnoticed inconsistencies in the ER schemas and in implicit ramifications of the modeling that have not been intended by the designer. To address this problem, Description Logics (DLs) have been proposed and succesfully used as a tool for reasoning about ER diagrams and thereby detecting the aforementioned anomalies [5, 6, 8].
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Nechaev, V., Володимир Миколайович Соловйов, and A. Nagibas. Complex economic systems structural organization modelling. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1118.

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One of the well-known results of the theory of management is the fact, that multi-stage hierarchical organization of management is unstable. Hence, the ideas expressed in a number of works by Don Tapscott on advantages of network organization of businesses over vertically integrated ones is clear. While studying the basic tendencies of business organization in the conditions of globalization, computerization and internetization of the society and the results of the financial activities of the well-known companies, the authors arrive at the conclusion, that such companies, as IBM, Boeing, Mercedes-Benz and some others companies have not been engaged in their traditional business for a long time. Their partner networks performs this function instead of them. The companies themselves perform the function of system integrators. The Tapscott’s idea finds its confirmation within the framework of a new powerful direction of the development of the modern interdisciplinary science – the theory of the complex networks (CN) [2]. CN-s are multifractal objects, the loss of multifractality being the indicator of the system transition from more complex state into more simple state. We tested the multifractal properties of the data using the wavelet transform modulus maxima approach in order to analyze scaling properties of our company. Comparative analysis of the singularity spectrumf(®), namely, the difference between maximum and minimum values of ® (∆ = ®max ¡ ®min) shows that IBM company is considerably more fractal in comparison with Apple Computer. Really, for it the value of ∆ is equal to 0.3, while for the vertically integrated company Apple it only makes 0.06 – 5 times less. The comparison of other companies shows that this dependence is of general character. Taking into consideration the fact that network organization of business has become dominant in the last 5-10 years, we carried out research for the selected companies in the earliest possible period of time which was determined by the availability of data in the Internet, or by historically later beginning of stock trade of computer companies. A singularity spectrum of the first group of companies turned out to be considerably narrower, or shifted toward the smaller values of ® in the pre-network period. The latter means that dynamic series were antipersistant. That is, these companies‘ management was rigidly controlled while the impact of market mechanisms was minimized. In the second group of companies if even the situation did changed it did not change for the better. In addition, we discuss applications to the construction of portfolios of stock that have a stable ratio of risk to return.
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Omino, Akira. Working paper PUEAA No. 13. Contesting Space in Postwar Tokyo's Sanya Day Labor District. Universidad Nacional Autónoma de México, Programa Universitario de Estudios sobre Asia y África, 2022. http://dx.doi.org/10.22201/pueaa.011r.2022.

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This article examines a series of day laborer riots that occurred between 1959 and 1962 in Tokyo's largest day laborer district, Sanya. In doing so, it attempts to understand how local social changes were related to the riots. This paper argues that these riots represent a radical reaction on the part of Sanya's day laborers to the complex macroeconomic changes accompanying the era of high-speed growth. These changes, intimately related to the domestic construction industry, transformed Sanya into a profitable urban space in which capital could be invested and value generated.
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Perdigão, Rui A. P., and Julia Hall. Spatiotemporal Causality and Predictability Beyond Recurrence Collapse in Complex Coevolutionary Systems. Meteoceanics, November 2020. http://dx.doi.org/10.46337/201111.

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Causality and Predictability of Complex Systems pose fundamental challenges even under well-defined structural stochastic-dynamic conditions where the laws of motion and system symmetries are known. However, the edifice of complexity can be profoundly transformed by structural-functional coevolution and non-recurrent elusive mechanisms changing the very same invariants of motion that had been taken for granted. This leads to recurrence collapse and memory loss, precluding the ability of traditional stochastic-dynamic and information-theoretic metrics to provide reliable information about the non-recurrent emergence of fundamental new properties absent from the a priori kinematic geometric and statistical features. Unveiling causal mechanisms and eliciting system dynamic predictability under such challenging conditions is not only a fundamental problem in mathematical and statistical physics, but also one of critical importance to dynamic modelling, risk assessment and decision support e.g. regarding non-recurrent critical transitions and extreme events. In order to address these challenges, generalized metrics in non-ergodic information physics are hereby introduced for unveiling elusive dynamics, causality and predictability of complex dynamical systems undergoing far-from-equilibrium structural-functional coevolution. With these methodological developments at hand, hidden dynamic information is hereby brought out and explicitly quantified even beyond post-critical regime collapse, long after statistical information is lost. The added causal insights and operational predictive value are further highlighted by evaluating the new information metrics among statistically independent variables, where traditional techniques therefore find no information links. Notwithstanding the factorability of the distributions associated to the aforementioned independent variables, synergistic and redundant information are found to emerge from microphysical, event-scale codependencies in far-from-equilibrium nonlinear statistical mechanics. The findings are illustrated to shed light onto fundamental causal mechanisms and unveil elusive dynamic predictability of non-recurrent critical transitions and extreme events across multiscale hydro-climatic problems.
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Соловйов, В. М., and В. В. Соловйова. Моделювання мультиплексних мереж. Видавець Ткачук О.В., 2016. http://dx.doi.org/10.31812/0564/1253.

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From the standpoint of interdisciplinary self-organization theories and synergetics analyzes current approaches to modeling socio-economic systems. It is shown that the complex network paradigm is the foundation on which to build predictive models of complex systems. We consider two algorithms to transform time series or a set of time series to the network: recurrent and graph visibility. For the received network designed dynamic spectral, topological and multiplex measures of complexity. For example, the daily values the stock indices show that most of the complexity measures behaving in a characteristic way in time periods that characterize the different phases of the behavior and state of the stock market. This fact encouraged to use monitoring and prediction of critical and crisis states in socio-economic systems.
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Patterson, P. E. The Complete Fast Fourier Transform and Cascaded Transition-Band Filters to Reduce the Noise of Deconvolution. Office of Scientific and Technical Information (OSTI), January 2000. http://dx.doi.org/10.2172/776348.

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10

Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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Abstract:
This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are obtained by manual sampling of the filed in a grid pattern. Maps of various field attributes are then prepared from these samples by the "Inverse Distance" interpolation method or by Kriging. An improved interpolation method was developed which is based on minimizing the overall curvature of the resulting map. Such maps are the ground truth reference, used for training the algorithm that generates the predicted field maps from remote sensing imagery. Both the reference and the predicted maps are stratified into "Prototype Plots", e.g. 15xl5 blocks of 2m pixels whereby the block size is 30x30m. This averaging reduces the datasets to manageable size and significantly improves the typically poor repeatability of remote sensing imaging systems. In the first two years of the project we used the Normalized Difference Vegetation Index (NDVI), for generating predicted yield maps of sugar beets and com. The NDVI was computed from image cubes of three spectral bands, generated by an optically filtered three camera video imaging system. A two dimensional FFT based regression model Y=f(X), was used wherein Y was the reference map and X=NDVI was the predictor. The FFT regression method applies the "Wavelet Based", "Pixel Block" and "Image Rotation" transforms to the reference and remote images, prior to the Fast - Fourier Transform (FFT) Regression method with the "Phase Lock" option. A complex domain based map Yfft is derived by least squares minimization between the amplitude matrices of X and Y, via the 2D FFT. For one time predictions, the phase matrix of Y is combined with the amplitude matrix ofYfft, whereby an improved predicted map Yplock is formed. Usually, the residuals of Y plock versus Y are about half of the values of Yfft versus Y. For long term predictions, the phase matrix of a "field mask" is combined with the amplitude matrices of the reference image Y and the predicted image Yfft. The field mask is a binary image of a pre-selected region of interest in X and Y. The resultant maps Ypref and Ypred aremodified versions of Y and Yfft respectively. The residuals of Ypred versus Ypref are even lower than the residuals of Yplock versus Y. The maps, Ypref and Ypred represent a close consensus of two independent imaging methods which "view" the same target. In the last two years of the project our remote sensing capability was expanded by addition of a CASI II airborne hyperspectral imaging system and an ASD hyperspectral radiometer. Unfortunately, the cross-noice and poor repeatability problem we had in multi-spectral imaging was exasperated in hyperspectral imaging. We have been able to overcome this problem by over-flying each field twice in rapid succession and developing the Repeatability Index (RI). The RI quantifies the repeatability of each spectral band in the hyperspectral image cube. Thereby, it is possible to select the bands of higher repeatability for inclusion in the prediction model while bands of low repeatability are excluded. Further segregation of high and low repeatability bands takes place in the prediction model algorithm, which is based on a combination of a "Genetic Algorithm" and Partial Least Squares", (PLS-GA). In summary, modus operandi was developed, for deriving important plant growth attribute maps (yield, leaf nitrate, biomass and sugar percent in beets), from remote sensing imagery, with sufficient accuracy for precision cropping applications. This achievement is remarkable, given the inherently high cross-noice between the reference and remote imagery as well as the highly non-repeatable nature of remote sensing systems. The above methodologies may be readily adopted by commercial companies, which specialize in proving remotely sensed data to farmers.
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