Relevant bibliographies by topics / ANN

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'ANN'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "ANN"

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Suhartina, Febby E. F. Kandou, and Marina F. O. Singkoh. "Isolasi dan Identifikasi Jamur Endofit Pada Tumbuhan Paku Asplenium nidus." Jurnal MIPA 7, no. 2 (July 1, 2018): 24. http://dx.doi.org/10.35799/jm.7.2.2018.20640.

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Penelitian ini bertujuan untuk mengisolasi dan mengidentifikasi jamur endofit pada tumbuhan paku Asplenium nidus. Metode yang digunakan dalam penelitian ini adalah isolasi jamur endofit, pemurnian jamur endofit, dan identifikasi jamur endofit secara makroskopik dan mikroskopik. Hasil isolasi dan pemurnian jamur endofit diperoleh lima isolat jamur endofit yaitu AN1, AN2, AN3, AN4 dan AN5. Teridentifikasi sebagai genus Gliocladium, Neoscytalidium, Humicola, Phialophoroides dan Aspergillus.This study aims to isolate and identify endophytic fungi in Asplenium nidus. The method used in this research is endophytic fungal isolation, purification of endophytic fungi, and identification of macroscopic and microscopic endophytic fungi. Results of isolation and purification of endophytic fungi obtained five endofit fungal isolates are AN1, AN2, AN3, AN4 and AN5. Identified as genus Gliocladium, Neoscytalidium, Humicola, Phialophoroides and Aspergillus.
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Mahapatra, Jayanta. "Ann." Hudson Review 39, no. 1 (1986): 95. http://dx.doi.org/10.2307/3851619.

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Stricklin-Parker, Ericka, and Barry A. Schneider. "Ann." Clinical Case Studies 4, no. 4 (October 2005): 315–28. http://dx.doi.org/10.1177/1534650105277713.

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Chen, Wei Lun, and Gong Cai Xin. "Research on ANN Dynamic Inversion Control of UAV." Advanced Materials Research 466-467 (February 2012): 1353–57. http://dx.doi.org/10.4028/www.scientific.net/amr.466-467.1353.

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The paper proposes a method to design AANN dynamic inversion controller through online ANN compensating inversion error. It mainly aims at evident shortage of dynamic inversion controller of UAV. A single hidden layer ANN structure is constructed and the stability of the whole closed loop system is proved. Also the stable adjustment arithmetic of online ANN weight is proposed. The robustness, the adaptability to fault and the response capability to actuator delay time of the scheme are verified by simulation. It is also proved that the online ANN has improved the performance of dynamic inversion controller well. It has important reference value for designing advanced flight control systems of UAV.
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Lu, P. J., M. C. Zhang, T. C. Hsu, and J. Zhang. "An Evaluation of Engine Faults Diagnostics Using Artificial Neural Networks." Journal of Engineering for Gas Turbines and Power 123, no. 2 (January 1, 2001): 340–46. http://dx.doi.org/10.1115/1.1362667.

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Application of artificial neural network (ANN)-based method to perform engine condition monitoring and fault diagnosis is evaluated. Back-propagation, feedforward neural nets are employed for constructing engine diagnostic networks. Noise-contained training and testing data are generated using an influence coefficient matrix and the data scatters. The results indicate that under high-level noise conditions ANN fault diagnosis can only achieve a 50–60 percent success rate. For situations where sensor scatters are comparable to those of the normal engine operation, the success rates for both four-input and eight-input ANN diagnoses achieve high scores which satisfy the minimum 90 percent requirement. It is surprising to find that the success rate of the four-input diagnosis is almost as good as that of the eight-input. Although the ANN-based method possesses certain capability in resisting the influence of input noise, it is found that a preprocessor that can perform sensor data validation is of paramount importance. Autoassociative neural network (AANN) is introduced to reduce the noise level contained. It is shown that the noise can be greatly filtered to result in a higher success rate of diagnosis. This AANN data validation preprocessor can also serve as an instant trend detector which greatly improves the current smoothing methods in trend detection. It is concluded that ANN-based fault diagnostic method is of great potential for future use. However, further investigations using actual engine data have to be done to validate the present findings.
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Rice, Robin, and Joan Simon. "Ann Hamilton." Woman's Art Journal 24, no. 2 (2003): 37. http://dx.doi.org/10.2307/1358786.

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Green, Andrew. "Ann McGuiness." Lancet 400, no. 10359 (October 2022): 1190. http://dx.doi.org/10.1016/s0140-6736(22)01895-5.

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Lequenne, Michel. "Ann Radcliffe." Cahiers du féminisme 47, no. 1 (1988): 36–38. http://dx.doi.org/10.3406/cafem.1988.3817.

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Zhao, Kang, Liuyihan Song, Yingya Zhang, Pan Pan, Yinghui Xu, and Rong Jin. "ANN softmax." Proceedings of the VLDB Endowment 15, no. 1 (September 2021): 1–10. http://dx.doi.org/10.14778/3485450.3485451.

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Thanks to the popularity of GPU and the growth of its computational power, more and more deep learning tasks, such as face recognition, image retrieval and word embedding, can take advantage of extreme classification to improve accuracy. However, it remains a big challenge to train a deep model with millions of classes efficiently due to the huge memory and computation consumption in the last layer. By sampling a small set of classes to avoid the total classes calculation, sampling-based approaches have been proved to be an effective solution. But most of them suffer from the following two issues: i) the important classes are ignored or only partly sampled, such as the methods using random sampling scheme or retrieval techniques of low recall (e.g., locality-sensitive hashing), resulting in the degradation of accuracy; ii) inefficient implementation owing to incompatibility with GPU, like selective softmax. It uses hashing forest to help select classes, but the search process is implemented in CPU. To address the above issues, we propose a new sampling-based softmax called ANN Softmax in this paper. Specifically, we employ binary quantization with inverted file system to improve the recall of important classes. With the help of dedicated kernel design, it can be totally parallelized in mainstream training framework. Then, we find the size of important classes that are recalled by each training sample has a great impact on the final accuracy, so we introduce sample grouping optimization to well approximate the full classes training. Experimental evaluations on two tasks (Embedding Learning and Classification) and ten datasets (e.g., MegaFace, ImageNet, SKU datasets) demonstrate our proposed method maintains the same precision as Full Softmax for different loss objectives, including cross entropy loss, ArcFace, CosFace and D-Softmax loss, with only 1/10 sampled classes, which outperforms the state-of-the-art techniques. Moreover, we implement ANN Soft-max in a complete GPU pipeline that can accelerate the training more than 4.3X. Equipped our method with a 256 GPUs cluster, the time of training a classifier of 300 million classes on our SKU-300M dataset can be reduced to ten days.
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Wright, Jay. "Ann Street." Callaloo, no. 27 (1986): 309. http://dx.doi.org/10.2307/2930650.

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Dissertations / Theses on the topic "ANN"

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Kößler, Ann-Kathrin. "An experimental investigation of moral commitments." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/86098/1/Ann-Kathrin_Koessler_Thesis.pdf.

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This thesis explored the impact of non-contractual agreements in economic decisions. These statements of intent serve as a commitment device in strategic decisions and have been found to be an effective alternative to strong regulations in promoting social behaviour. Three studies have been undertaken using conceptual and methodological approaches from Behavioral and Experimental Economics. The first study explored in a public good setting the effect of public statements about intended social behaviour. The second study tested whether promises can help to promote co-operation in environments with uncertain choice options. The third study investigated a possible application of statement of intent and tested the effect of payment promises in a tax setting.
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Mineiro, Maria Teresa Luz. "Reflexões sobre o estágio ann demeulemeester. Reflections on the internship: ann demeulemeester." Master's thesis, Universidade de Lisboa. Faculdade de Arquitetura, 2013. http://hdl.handle.net/10400.5/6610.

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Pearson, Mary. "Ann Richards : An Adlerian Psychobiography." Thesis, University of North Texas, 1992. https://digital.library.unt.edu/ark:/67531/metadc277775/.

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This psychobiography used the framework of Individual Psychology to examine the life style development of the Honorable Ann Richards in order to provide insight into the creation of a life style by a successful, contemporary female leader. This single case study utilized a qualitative/phenomenological research methodology to examine from Ms. Richards' point of view the manner in which a highly visible and well-known individual created her particular style of life.
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Armstrong, Timothy Currie. "Stèidheachadh Ghnàthan-cànain Ùra Cuairteachadh Ideòlais-chànain ann an Trì Gaeltachtaí Nua." Thesis, University of the Highlands and Islands, 2009. https://pure.uhi.ac.uk/portal/en/studentthesis/steidheachadh-ghnathancanain-ura-cuairteachadh-ideolaischanain-ann-an-tri-gaeltachtai-nua(6e65c8cc-0ea2-4d13-a475-9f13aa7a353f).html.

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Chaidh trì Gaeltachtaí nua a sgrùdadh mar eisimpleirean de dhealbhadh-cànain ann am buidhnean beaga agus aig a' mhion-ìre: Coimhearsnachd Bhóthar Seoighe ann am Béal Feirste, Èirinn a Tuath, Scéim Chónaithe Choláiste na Tríonóide ann am Baile Átha Cliath, Poblach na h-Èireann agus Sgìre Charn Tóchair ann an Contae Dhoire a Deas, Èirinn a Tuath. Bhiodh na trì coimhearsnachdan seo coltach ri chèile anns an t-seagh gum biodh iad uile ag iomairt gus làraichean còmhnaidheach a stèidheachadh far an rachadh cleachdadh Gàidhlig na h-Èireann na ghnàths gu ìre no eile. Chaidh gnìomh an ideòlais-chànain a mheasadh anns na Gaeltachtaí nua, agus gu sònraichte, sgrùdadh mar a chaidh gnàthan-cànain Ghàidhlig a stèidheachadh agus a dhìon anns na coimhearsnachdan. An toiseach, rinneadh rannsachadh air ideòlas-cànain coiteanta a nochd anns na pàipearan-naidheachd ann am Poblachd na h-Èireann agus Èirinn a Tuath gus seòrsachadh a thrusadh de dh'ideòlasan cumanta ann an Èirinn, agus mar sin, gus dealbh a tharraing dhen àrainneachd ideòlaich far am biodh na Gaeltachtaí nua suidhichte. An uair sin, chaidh gach coimhearsnachd a sgrùdadh fa leth, le sùil air a' cheangal eadar structar nan coimhearsnachdan agus gnìomh an ideòlais nam broinn. Mu dheireadh, rinneadh triantanachadh dhe na toraidhean bho na trì làraicheanrannsachaidh eadar-dhealaichte gus ginearalachadh mu ghnìomh an ideòlais-chànain ann am buidhnean beaga, agus mheòraicheadh air cuid dhe na teamaichean coitcheann a chaidh a lorg. Gu sònraichte, shealladh mar a chuir am miann air nàdarrachd ann an labhairt bacadh air èifeachd stèidheachadh nan gnàthan-cànain Ghàidhlig ùra anns na Gaeltachtaí nua agus thaisbeineadh molaidhean dèantach a thaobh ath-leasachaidhcànain aig a' mhion-ìre a dh'èirich às an rannsachadh.
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Linder, Niklas. "ARTIFICIELL INTELLIGENS : Vägplanering med ANN." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11080.

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Detta arbete undersöker hur väl agenter styrda av artificiella neurala nätverk (ANN) klarar av att lösa vägplaneringsproblem. Agenternas beteende kommer även tränas med hjälp av en evolutionär algoritm. Vi kommer utvärdera agenternas förmåga att navigera sig mot mål och undvika hinder i dess väg. En jämförelse med A* kommer göras med hänsyn på funktionalitet och realism. Genomförandet gick kortfattat ut på att skapa en mängd experimentmiljöer med olika svårighetsgrader där agenterna kunde tränas. Resultaten visade att ANN-styrda agenter inte hade något större problem att lösa vägplaneringsproblem men hade svårare att undvika hinder. Vägarna var inte lika optimerade som A*-vägar men hade mjukare svängar. Något som inte fokuserats tillräckligt på i detta arbete är att försöka skapa ett större medvetande hos det neurala närtverket. Ett tillvägagångsätt att undersöka detta skulle kunna vara att förändra arkitekturens storlek samt implementering av minne.
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Pogemaa, Joel. "Kombination av exempelbaserad och belöningsbaserad inlärning för ANN." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-17064.

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Det här experimentet gick ut på att testa tre olika inlärningsstrategier emot varandra i en spelmiljö. De tre inlärningsstrategier som testades var en exempelbaserad strategi, en belöningsbaserad strategi och en strategi som kombinerade dessa två algoritmer. Kombinationen bestod av att först träna upp ett nätverk med den exempelbaserade strategin för att sedan använda det nätverket som en utgångspunkt för den belöningsbaserade strategin. Dessa strategier testades sedan i en spelmiljö. Resultatet som de olika strategierna producerade var svårtolkade. På grund av att alla inlärningsstrategierna inte förbättrade sig märkvärdigt under deras träningstid har det gjort att resultaten från att ändra på variablerna hos de olika strategierna inte visat på några märkvärda skillnader i resultat. Skillnader i resultat vid jämförelser av de olika strategierna har observerats men det går inte att säkerställa att det är inlärningsstrategierna som är anledningen till skillnad i resultat.
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Manjunatha, Narigudde Nikethan Cheraghi Hossein S. "ANN model to predict burr height and thickness." Diss., A link to full text of this thesis in SOAR, 2007. http://soar.wichita.edu/dspace/handle/10057/1147.

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Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering.
"May 2007." Title from PDF title page (viewed on Dec. 27, 2007). Thesis adviser: Hossein S. Cheraghi. Includes bibliographic references (leaves 58-61).
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SHIVANI. "RESERVOIR OPERATIONS USING HYBRID MODELLING - ANN AND FNN." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18788.

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In this study, an attempt has been made to study reservoir operations using different technologies to check for their efficiency in predicting the water supply release and comparing it with the demands to be met. A hybrid modelling comprising of ANN and FNN has been used. ANN has the ability to predict the output data by assigning weights to the input variables based on its learning ability while FNN has an advantage of making decisions based on the logical inferences of fuzzy rules. The system considered for study purposes in this project is multipurpose reservoir dam across Sutlej river- Bhakra reservoir also known as Govind Sagar Reservoir situated in Una and Bilaspur district of Himachal Pradesh. Combining these two model for reservoir operations of Bhakra reservoir will improve the efficiency of operations of reservoir during critical time period. From the results it was observed that the improvement in the performance of reservoir operations were significant emphasizing on the use of AI methods such as ANN and FNN. Storage capacity, inflow into the reservoir and Evaporation losses were considered as independent parameters for the modelling the operations of ANN and FNN. These input parameters are tested for randomness and any correlations using the regression analysis method. Linear regression method for prediction of release is also effective but is not suggested because of numerous computations involved, this may result in confusion and chaos. Hence, the hybrid model of ANN and FNN is regarded as the most suited one for reservoir operations. Along with this an attempt has been made to predict the release and compare the same graphically using programming language such as Python. The algorithms of ANN, Random Forest and XGBosst has been used as these operates on the principle of Decision Trees and hence are considered effective for prediction and comparison purpose.
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Figge, Christian [Verfasser], Ann-Kristin [Akademischer Betreuer] Achleitner, and Christoph [Akademischer Betreuer] Kaserer. "Essays on Secondary Buyouts / Christian Figge. Gutachter: Ann-Kristin Achleitner ; Christoph Kaserer. Betreuer: Ann-Kristin Achleitner." München : Universitätsbibliothek der TU München, 2012. http://d-nb.info/1031514902/34.

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Lu, Ming. "Productivity studies using advanced ANN models." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0012/NQ60322.pdf.

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Books on the topic "ANN"

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Major, Kevin. Ann and Seamus. Toronto: Douglas & McIntyre, 2003.

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French, Edith. Connie and Ann. London: Constable, 1986.

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Major, Kevin. Ann and Seamus. Toronto: Groundwood Books, 2003.

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Salzmann, Mary Elizabeth. Ann and Alan. Edina, Minn: ABDO Pub. Co., 2005.

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Parker, Thomas Trebitsch. Anna, Ann, Annie. New York, N.Y., U.S.A: Penguin Books, 1993.

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French, Edith. Connie and Ann. London: Constable, 1986.

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Parker, Thomas Trebitsch. Anna, Ann, Annie. New York: Plume, 1994.

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ill, Dewey Ariane, ed. Sally Ann Thunder Ann Whirlwind Crockett. New York: Greenwillow Books, 1985.

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Cohen, Caron Lee. Sally Ann Thunder Ann Whirlwind Crockett. New York: Mulberry Paperback Book, 1993.

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Wells, H. G. Ann Veronica. London: Dent, 1993.

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Book chapters on the topic "ANN"

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Lethbridge, Stefanie, and Walter Kluge. "Ann Radcliffe." In Kindler Kompakt: Horrorliteratur, 38–42. Stuttgart: J.B. Metzler, 2017. http://dx.doi.org/10.1007/978-3-476-04502-7_4.

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Tait, Ruth. "Ann Iverson." In Roads to the Top, 111–28. London: Palgrave Macmillan UK, 1995. http://dx.doi.org/10.1007/978-1-349-13669-8_8.

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Herrmann, Elisabeth. "Jäderlund, Ann." In Kindlers Literatur Lexikon (KLL), 1. Stuttgart: J.B. Metzler, 2020. http://dx.doi.org/10.1007/978-3-476-05728-0_9394-1.

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Heinen, Sandra. "Yearsley, Ann." In Kindlers Literatur Lexikon (KLL), 1. Stuttgart: J.B. Metzler, 2020. http://dx.doi.org/10.1007/978-3-476-05728-0_17452-1.

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Patanella, Daniel, and Chandra Ebanks. "Anastasi, Ann." In Encyclopedia of Child Behavior and Development, 93–94. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-79061-9_131.

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Gad, Ahmed Fawzy. "ANN Optimization." In Practical Computer Vision Applications Using Deep Learning with CNNs, 129–81. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-4167-7_4.

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Raphael-Hernandez, Heike. "Petry, Ann." In Kindlers Literatur Lexikon (KLL), 1. Stuttgart: J.B. Metzler, 2020. http://dx.doi.org/10.1007/978-3-476-05728-0_12313-1.

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Lethbridge, Stefanie. "Radcliffe, Ann." In Kindlers Literatur Lexikon (KLL), 1. Stuttgart: J.B. Metzler, 2020. http://dx.doi.org/10.1007/978-3-476-05728-0_14538-1.

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Nunn, Hillary. "Fanshawe, Ann." In The Palgrave Encyclopedia of Early Modern Women's Writing, 1–3. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-01537-4_127-3.

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Thaler, Ingrid. "Beattie, Ann." In Kindlers Literatur Lexikon (KLL), 1. Stuttgart: J.B. Metzler, 2020. http://dx.doi.org/10.1007/978-3-476-05728-0_4879-1.

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Conference papers on the topic "ANN"

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"Proceedings of the First International Forum on Applications of Neural Networks to Power Systems (Cat. No.91TH0374-9)." In Proceedings of the First International Forum on Applications of Neural Networks to Power Systems. IEEE, 1991. http://dx.doi.org/10.1109/ann.1991.213528.

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"ANNPS '93. Proceedings of the Second International Forum on Applications of Neural Networks to Power Systems (Cat. No.93TH0532-2)." In Second International Forum on Applications of Neural Networks to Power Systems. IEEE, 1993. http://dx.doi.org/10.1109/ann.1993.264359.

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Li, Guangli, Guancheng Wang, Qiang Wang, Fan Fei, Shuai Lü, and Degui Guo. "ANN." In the 2016 International Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/3028842.3028893.

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Khan, Kashif, Saddam Husain, Galymzhan Nauryzbayev, and Mohammad Hashmi. "Development and Evaluation of ANN, ACOR-ANN, ALO-ANN Based Small-Signal Behavioral Models for GaN-on-Si HEMT." In 2023 30th IEEE International Conference on Electronics, Circuits and Systems (ICECS). IEEE, 2023. http://dx.doi.org/10.1109/icecs58634.2023.10382905.

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Nosratabadi, Saeed, Karoly Szell, Bertalan Beszedes, Felde Imre, Sina Ardabili, and Amir Mosavi. "Comparative Analysis of ANN-ICA and ANN-GWO for Crop Yield Prediction." In 2020 RIVF International Conference on Computing and Communication Technologies (RIVF). IEEE, 2020. http://dx.doi.org/10.1109/rivf48685.2020.9140786.

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Soren, Rohit Anand, Nishant Kumar, and Praveen Kumar. "Comparison Analysis of Maximum Power Point Tracking Between ANN and Cascade ANN." In 2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC). IEEE, 2022. http://dx.doi.org/10.1109/isssc56467.2022.10051422.

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Jarndal, Anwar, and Saddam Husain. "Forecasting of Electric Peak Load Using ANN-Cascaded, ANN-NARX and GPR Techniques." In 2020 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI). IEEE, 2020. http://dx.doi.org/10.1109/ccci49893.2020.9256555.

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Zhang, Menghao, Jiasong Bai, Guanyu Li, Zili Meng, Hongda Li, Hongxin Hu, and Mingwei Xu. "When NFV Meets ANN: Rethinking Elastic Scaling for ANN-based NFs." In 2019 IEEE 27th International Conference on Network Protocols (ICNP). IEEE, 2019. http://dx.doi.org/10.1109/icnp.2019.8888133.

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Fiskin, Cemile Solak, and A. Guldem Cerit. "Forecasting Domestic Shipping Demand of Cement: Comparison of SARIMAX, ANN and Hybrid SARIMAX-ANN." In 2019 4th International Conference on Computer Science and Engineering (UBMK). IEEE, 2019. http://dx.doi.org/10.1109/ubmk.2019.8907210.

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Tanzim, Nasir, Salih Nbhan, Tze Hui Liew, Chee Wen Chin, and B. F. Yousif. "ANN for Tribological Applications." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-10161.

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The current work is an attempt to investigate the possibility of using artificial neural network (ANN) modelling as a tool for friction coefficient prediction. The ANN model was trained at various configurations with different functions of training to develop the optimal ANN model. The experimental data was obtained from previous works. The results revealed that single layered model has reasonable accuracy in prediction when trained with TrainLM function. The results were acceptable especially in predicting steady-state friction coefficient, which proved ANN technology’s ability to predict the friction co-efficient.
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Reports on the topic "ANN"

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Deming, M. Elen, and Paul Littleton. Ann Arbor Municipal Center. Landscape Architecture Foundation, 2013. http://dx.doi.org/10.31353/cs0460.

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Keck, R. D. ,. Fluor Daniel Hanford. Operational test report ANN-714. Office of Scientific and Technical Information (OSTI), February 1997. http://dx.doi.org/10.2172/330708.

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Geisler, Nathan. Final Technical Report, Wind Generator Project (Ann Arbor). Office of Scientific and Technical Information (OSTI), March 2017. http://dx.doi.org/10.2172/1347227.

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Bilich, Andy, Brittany Staie, James McCall, Alexis Pascaris, Brian Mirletz, Thomas Hickey, Sudha Kannan, Sally Williams, Kai Lepley, and Jordan Macknick. Adapte Agrivoltayik Pou Mini-Rezo Sole Ann Ayiti. Office of Scientific and Technical Information (OSTI), March 2024. http://dx.doi.org/10.2172/2333638.

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Thorsteinsson, R. Geology, Bear Bay East and Lady Ann Strait, District of Franklin, Northwest Territories. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/122791.

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Warrick, Arthur W., Gideon Oron, Mary M. Poulton, Rony Wallach, and Alex Furman. Multi-Dimensional Infiltration and Distribution of Water of Different Qualities and Solutes Related Through Artificial Neural Networks. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7695865.bard.

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Abstract:
The project exploits the use of Artificial Neural Networks (ANN) to describe infiltration, water, and solute distribution in the soil during irrigation. It provides a method of simulating water and solute movement in the subsurface which, in principle, is different and has some advantages over the more common approach of numerical modeling of flow and transport equations. The five objectives were (i) Numerically develop a database for the prediction of water and solute distribution for irrigation; (ii) Develop predictive models using ANN; (iii) Develop an experimental (laboratory) database of water distribution with time; within a transparent flow cell by high resolution CCD video camera; (iv) Conduct field studies to provide basic data for developing and testing the ANN; and (v) Investigate the inclusion of water quality [salinity and organic matter (OM)] in an ANN model used for predicting infiltration and subsurface water distribution. A major accomplishment was the successful use of Moment Analysis (MA) to characterize “plumes of water” applied by various types of irrigation (including drip and gravity sources). The general idea is to describe the subsurface water patterns statistically in terms of only a few (often 3) parameters which can then be predicted by the ANN. It was shown that ellipses (in two dimensions) or ellipsoids (in three dimensions) can be depicted about the center of the plume. Any fraction of water added can be related to a ‘‘probability’’ curve relating the size of the ellipse (or ellipsoid) that contains that amount of water. The initial test of an ANN to predict the moments (and hence the water plume) was with numerically generated data for infiltration from surface and subsurface drip line and point sources in three contrasting soils. The underlying dataset consisted of 1,684,500 vectors (5 soils×5 discharge rates×3 initial conditions×1,123 nodes×20 print times) where each vector had eleven elements consisting of initial water content, hydraulic properties of the soil, flow rate, time and space coordinates. The output is an estimate of subsurface water distribution for essentially any soil property, initial condition or flow rate from a drip source. Following the formal development of the ANN, we have prepared a “user-friendly” version in a spreadsheet environment (in “Excel”). The input data are selected from appropriate values and the output is instantaneous resulting in a picture of the resulting water plume. The MA has also proven valuable, on its own merit, in the description of the flow in soil under laboratory conditions for both wettable and repellant soils. This includes non-Darcian flow examples and redistribution and well as infiltration. Field experiments were conducted in different agricultural fields and various water qualities in Israel. The obtained results will be the basis for the further ANN models development. Regions of high repellence were identified primarily under the canopy of various orchard crops, including citrus and persimmons. Also, increasing OM in the applied water lead to greater repellency. Major scientific implications are that the ANN offers an alternative to conventional flow and transport modeling and that MA is a powerful technique for describing the subsurface water distributions for normal (wettable) and repellant soil. Implications of the field measurements point to the special role of OM in affecting wettability, both from the irrigation water and from soil accumulation below canopies. Implications for agriculture are that a modified approach for drip system design should be adopted for open area crops and orchards, and taking into account the OM components both in the soil and in the applied waters.
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ALTIC, NICK A. INDEPENDENT CONFIRMATORY SURVEY SUMMARY AND RESULTS FOR THE FORD NUCLEAR REACTOR, ANN ARBOR, MICHIGAN. Office of Scientific and Technical Information (OSTI), July 2013. http://dx.doi.org/10.2172/1096531.

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OHM REMEDIATION SERVICES CORP PITTSBURGH PA. Ordnance Survey - 7,600-Acre Parcel, Fort George G. Meade, Ann Arundel County, Maryland. Fort Belvoir, VA: Defense Technical Information Center, December 1995. http://dx.doi.org/10.21236/ada316162.

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Yonemura, Ann. Art in Context: Aesthetics, Environment and Function in the Arts of Japan. Inter-American Development Bank, March 1995. http://dx.doi.org/10.18235/0007915.

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ALTIC, NICK A. "INDEPENDENT CONFIRMATORY SURVEY SUMMARY AND RESULTS FOR THE FORD NUCLEAR REACTOR, REVISION 1, ANN ARBOR, MICHIGAN. Office of Scientific and Technical Information (OSTI), August 2013. http://dx.doi.org/10.2172/1096532.

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