Bibliografias temáticas / RMSE

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Literatura científica selecionada sobre o tema "RMSE"

Autor: Grafiati
Publicado: 4 de junho de 2021
Última modificação: 25 de julho de 2025

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Artigos de revistas sobre o assunto "RMSE"

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Chai, T., and R. R. Draxler. "Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature." Geoscientific Model Development 7, no. 3 (2014): 1247–50. http://dx.doi.org/10.5194/gmd-7-1247-2014.

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Abstract. Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error, and thus the MAE would be a better metric for that purpose. While some concerns over using RMSE raised by Willmott and Matsuura (2005) and Willmott et al. (2009) are valid, the proposed avoidance of RMSE in favor of MAE is not the solution. Citing the aforementioned papers, many researchers chose MA
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Mentaschi, L., G. Besio, F. Cassola, and A. Mazzino. "Problems in RMSE-based wave model validations." Ocean Modelling 72 (December 2013): 53–58. http://dx.doi.org/10.1016/j.ocemod.2013.08.003.

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Chai, T., and R. R. Draxler. "Root mean square error (RMSE) or mean absolute error (MAE)?" Geoscientific Model Development Discussions 7, no. 1 (2014): 1525–34. http://dx.doi.org/10.5194/gmdd-7-1525-2014.

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Abstract. Both the root mean square error (RMSE) and the mean absolute error (MAE) are regularly employed in model evaluation studies. Willmott and Matsuura (2005) have suggested that the RMSE is not a good indicator of average model performance and might be a misleading indicator of average error and thus the MAE would be a better metric for that purpose. Their paper has been widely cited and may have influenced many researchers in choosing MAE when presenting their model evaluation statistics. However, we contend that the proposed avoidance of RMSE and the use of MAE is not the solution to t
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Hussain, Ruba Yousif, Abd ul-Razzak T. Ziboon, and Khalid I. Hassun. "STANDARD MBTHOD OF RMSE CALCULATION FROM POLYNOMIAL RECTIFICATION." Journal of Engineering 8, no. 04 (2002): 361–70. http://dx.doi.org/10.31026/j.eng.2002.04.07.

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Image quality and geometric accuracy of SPOT data are essential elements in cartographi: applications. The evaluation of geometric accuracy of SPOT data is carried out by analysis and quantification of the errors in geometric correction. For this purpose, many programs are designed to correct the image geometrically (polynomial transformation) and to calculate the root mea 1 square error (RMSE) by the standard method.
 The standard method of calculating the RMSE is shown to be capable of providing accurate estimates of geometric error when a modest number of control points is available (b
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Pranata, Adrian, Joshua Farragher, Luke Perraton, et al. "Impaired Lumbar Extensor Force Control Is Associated with Increased Lifting Knee Velocity in People with Chronic Low-Back Pain." Sensors 23, no. 21 (2023): 8855. http://dx.doi.org/10.3390/s23218855.

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The ability of the lumbar extensor muscles to accurately control static and dynamic forces is important during daily activities such as lifting. Lumbar extensor force control is impaired in low-back pain patients and may therefore explain the variances in lifting kinematics. Thirty-three chronic low-back pain participants were instructed to lift weight using a self-selected technique. Participants also performed an isometric lumbar extension task where they increased and decreased their lumbar extensor force output to match a variable target force within 20–50% lumbar extensor maximal voluntar
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Malik Bayu Aji. "Analisis Perbandingan RMSE Algoritma Machine Learning dalam Memprediksi Harga Saham." Jurnal Informatika dan Teknologi Komputer ( J-ICOM) 5, no. 2 (2024): 113–19. https://doi.org/10.55377/j-icom.v5i2.8265.

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Perkembangan teknologi bisnis membuat masyarakat tertarik dengan mengikuti bisnis berbasis daring salah satunya adalah perdagangan saham. Dalam melakukan perdagangan saham, diperlukan analisis mendalam terkait kondisi pasar agar tidak mengalami kerugian. Akan tetapi tidak semua orang mampu melakukan analisis pasar saham, pembelajaran mesin berperan penting dalam membantu analisis ini. Peneliti menggunakan metode simulasi dengan data historis saham PT. Telkom Indonesia periode 2018-2022 untuk membandingkan performa algoritma tersebut. Pada tahap percobaan, dilakukan pemodelan dan simulasi mengg
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Sugandi, Budi, and Yuniatmi Syamsudin. "Deteksi Tepi Canny dan RMSE untuk Identifikasi Kerusakan pada Kemasan Minuman." JURNAL INTEGRASI 14, no. 2 (2022): 110–13. http://dx.doi.org/10.30871/ji.v14i2.4420.

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Salah satu minuman kemasan yang banyak dipakai adalah kemasan kaleng. Kekurangan kemasan minuman kaleng adalah sifatnya yang mudah rusak akibat benturan dengan benda lain maupun terjatuh. Kemasan yang rusak mengakibatkan produk menjadi tidak sempurna. Sehingga proses identifikasi kerusakan kemasan kaleng menjadi sangat penting sebagai proses penjamin kualitas produk. Penelitian ini ditujukan sebagai salah satu solusi untuk mengidentifikasi kerusakan pada kemasan minuman kaleng. Metode deteksi yang diusulkan berdasarkan pada deteksi tepi Canny dan RMSE (Root Mean Square Error). Proses awal dete
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Lv, Xian Qiang, Song Yang, Xin Zhang, Ying Wang, Yun Feng Shi, and Liu Wei. "Fast Fractal Image Coding Method Based on RMSE and DCT Classification." Applied Mechanics and Materials 241-244 (December 2012): 3034–39. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.3034.

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To solve the problem of long time consuming in the fractal encoding process, a fast fractal encoding algorithm based on RMSE (Root mean square error) and DCT (Discrete Cosine Transform) classification is proposed. During the encoding process, firstly, the image is divided into range blocks and domain blocks by quadtree partition according to RMSE, then, according to DCT coefficients of image block, three classes of image blocks are defined, which are smooth class, horizontal/vertical edge class, diagonal/sub-diagonal class. At last, every range block is limited to search the best matched block
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Hindmarsh, Diane, and David Steel. "Estimating the RMSE of Small Area Estimates without the Tears." Stats 4, no. 4 (2021): 931–42. http://dx.doi.org/10.3390/stats4040054.

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Small area estimation (SAE) methods can provide information that conventional direct survey estimation methods cannot. The use of small area estimates based on linear and generalized linear mixed models is still very limited, possibly because of the perceived complexity of estimating the root mean square errors (RMSEs) of the estimates. This paper outlines a study used to determine the conditions under which the estimated RMSEs, produced as part of statistical output (‘plug-in’ estimates of RMSEs) could be considered appropriate for a practical application of SAE methods where one of the main
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Babu,, S. K. Khadar. "Mathematical Modelling of RMSE Approach on Agricultural Financial Data Sets." International Journal of Pure & Applied Bioscience 5, no. 6 (2017): 942–47. http://dx.doi.org/10.18782/2320-7051.5802.

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Teses / dissertações sobre o assunto "RMSE"

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SAH, BIKASH KUMAR. "A NOVEL CONVOLUTIONAL NEURAL NETWORK FOR AIR POLLUTION FORECASTING." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18792.

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Air pollution was a global problem a few decades back. It is still a problem and will continue to be a problem if not solved appropriately.Various machine learning and deep learining approaches have been purposed for accurate prediction, estimation and analysis of the air polution. We have purposed a novel five layer one-dimensional convolution neural network architecture to forecast the PM2.5 concentration. It is a deep learning approach. We have used the five year air pollution dataset from 2010 to 2014 recorded by the US embassy in Beijing, China taken from the database from UCI machi
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Chermiti, Amro. "Hur kan injicerad aktivitet individanpassas vid skelettscintigrafi? Effekten av patientspecifika parametrar." Thesis, Örebro universitet, Institutionen för hälsovetenskaper, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-84602.

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Bakgrund: Skelettscintigrafi är en nuklearmedicinsk undersökning. Undersökningen är den mest använda nukleardiagnostiska metoden och den genomförs ofta som en helkroppsundersökning. För att undersökningen ska kunna erhålla sin diagnostiska kvalitet, samt följa strålsäkerhetsmyndighetens rekommendationer behövs det mer kännedom till hur optimeringen ska följa as low as reasonably achievable (ALARA). Studiens syfte var att optimera patientstråldos samt att undersöka hur injicerad aktivitet kan anpassas efter patientens specifika parametrar. Metod: Studiegruppen bestod av 85 patienter som genomgi
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Hast, Isak. "Quality Assessment of Spatial Data: Positional Uncertainties of the National Shoreline Data of Sweden." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-18743.

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This study investigates on the planimetric (x, y) positional accuracy of the National Shoreline (NSL) data, produced in collaboration between the Swedish mapping agency Lantmäteriet and the Swedish Maritime Administration (SMA). Due to the compound nature of shorelines, such data is afflicted by substantial positional uncertainties. In contrast, the positional accuracy requirements of NSL data are high. An apparent problem is that Lantmäteriet do not measure the positional accuracy of NSL in accordance to the NSL data product specification. In addition, currently, there is little understanding
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Abdelhafeid, Faraj. "The Effect Upon Antenna Arrays of Variations of Element Orientation and Spacing in the Presence of Channel Noise, with an Application to Direction Finding." University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1525866099535246.

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Cantarello, Luca. "Analisi delle previsioni meteorologiche mensili mediante il modello GLOBO (ISAC-CNR)." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7690/.

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In questo lavoro sono presentate le principali caratteristiche delle previsioni meteorologiche mensili, nonché il progresso scientifico e storico che le ha coinvolte e le tecniche adibite alla loro verifica. Alcune di queste tecniche sono state applicate al fine di valutare ed analizzare l'errore sistematico (o bias) e l'RMSE di temperatura a 850 hPa (T850), altezza geopotenziale a 500 hPa (Z500) e precipitazioni cumulate del modello GLOBO, utilizzato presso l'Istituto per le Scienze dell'Atmosfera e del Clima del Consiglio Nazionale delle Ricerche per formulare previsioni mensili. I risultat
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Mansour, Tony, and Majdi Murtaja. "Applied estimation theory on power cable as transmission line." Thesis, Linnéuniversitetet, Institutionen för fysik och elektroteknik (IFE), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-46583.

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This thesis presents how to estimate the length of a power cable using the MaximumLikelihood Estimate (MLE) technique by using Matlab. The model of the power cableis evaluated in the time domain with additive white Gaussian noise. The statistics havebeen used to evaluate the performance of the estimator, by repeating the experiment fora large number of samples where the random additive noise is generated for each sample.The estimated sample variance is compared to the theoretical Cramer Raw lower Bound(CRLB) for unbiased estimators. At the end of thesis, numerical results are presentedthat sho
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Reigota, Nilvana dos Santos. "Comparação da transformada wavelet discreta e da transformada do cosseno, para compressão de imagens de impressão digital." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-27042007-101810/.

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Este trabalho tem por objetivo comparar os seguintes métodos de compressão de imagens de impressão digital: transformada discreta do cosseno (DCT), transformada de wavelets de Haar, transformada de wavelets de Daubechies e transformada de wavelets de quantização escalar (WSQ). O propósito da comparação é identificar o método que resulta numa menor perda de dados, para a maior taxa de compressão possível. São utilizadas as seguintes métricas para avaliação da qualidade da imagem para os métodos: erro quadrático médio (ERMS), a relação sinal e ruído (SNR) e a relação sinal ruído de pico (PSNR).
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Khurram, Jassal Muhammad. "The Effect of Optimization of Error Metrics." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20471.

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It is important for a retail company to forecast its sale in correct and accurate way to be ableto plan and evaluate sales and commercial strategies. Various forecasting techniques areavailable for this purpose. Two popular modelling techniques are Predictive Modelling andEconometric Modelling. The models created by these techniques are used to minimize thedifference between the real and the predicted values. There are several different errormetrics that can be used to measure and describe the difference. Each metric focuses ondifferent properties in the forecasts and it is hence important whi
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Laskauskas, Ramūnas. "Vaizdo kontūrų nustatymo būdų analizė." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080929_113638-76811.

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Vaizdo kontūrų nustatymo metodų tyrimui buvo pasirinktas 100 įvairaus turinio paveikslų su įvairiu elementų dydžiu ir skaičiumi. Tyrimui buvo pasirinkti 8 populiariausi vaizdo kontūrų nustatymo metodai: Canny, Sobel, Prewitt, Roberts, Zerocross, Laplacian, LoG, Marr-Hildreth. Atliekant tyrimus visiems paveikslams, naudojant visus 8 metodus, buvo subjektyviai parinkta optimaliausia slenkstinė reikšmė. Gavus visų 100 įvairių paveikslų geriausias slenkstines reikšmes su visais 8 metodais, buvo nustatytos slenkstinių reikšmių kitimo ribos kiekvienam kontūro išskyrimo metodui. Kiekvienam paveikslui
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Morelli, Stefano. "Optimal pose selection for the calibration of an overconstrained Cable-Driven Parallel Robot." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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In this project an optimal pose selection method for the calibration of an overconstrained Cable-Driven Parallel robot is presented. This manipulator belongs to a subcategory of parallel robots, where the classic rigid "legs" are replaced by cables. Cables are flexible elements that bring advantages and disadvantages to the robot modeling. For this reason, there are many open research issues, and the calibration of geometric parameters is one of them. The identification of the geometry of a robot, in particular, is usually called Kinematic Calibration. Many methods have been proposed in
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Livros sobre o assunto "RMSE"

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Wix, Györgyné. Régi magyarországi szerzők (RMSz). Országos Széchenyi Könyvtár, 2008.

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Minkov, Todor. Dve pobedi na RMS: Pŭrvii͡a︡t kongres na RMS, prot͡s︡esŭt sreshtu T͡S︡K na RMS. "Nar. mladezh", 1989.

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Chen, Derek Hung Chiat. The rmsm-x+p: A minimal poverty module for the rmsm-x. World Bank, 2004.

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Cooper, Suzanne Tarbell. RMS Queen Mary. Arcadia Pub., 2010.

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Stoĭkov, Mari͡an. Nashii͡at RMS: Spomeni. Nar. mladezh, 1989.

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Scheiblich, Reinhard. Leuchttu˜rme-Lexikon. 4th ed. Ed. Ellert & Richter, 2010.

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Everaert, Luc. A RMSM-X model for Turkey. Country Economics Dept., World Bank, 1990.

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Tonchev, I. N. RMS i sotsialisticheskata revoliutsiia. Nar. mladezh, 1985.

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Hind, Andrew. RMS Segwun: Queen of Muskoka. Dundurn, 2012.

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Go˜ttner, Heide Solveig. Die Priesterin der Tu˜rme. Piper, 2006.

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Capítulos de livros sobre o assunto "RMSE"

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Su, Yong, and Qingchuan Zhang. "Quality Assessment of Speckle Patterns by Estimating RMSE." In International Digital Imaging Correlation Society. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51439-0_17.

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Li, Wang, Xiaoan Tang, and Junda Zhang. "SRG and RMSE-Based Automated Segmentation for Volume Data." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71598-8_18.

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Haut, Nathan, Wolfgang Banzhaf, and Bill Punch. "Correlation Versus RMSE Loss Functions in Symbolic Regression Tasks." In Genetic and Evolutionary Computation. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8460-0_2.

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Ariyarathna, Imaya, and Katsuo Sasahara. "Procedure of Data Processing for the Improvement of Failure Time Prediction of a Landslide Based on the Velocity and Acceleration of the Displacement." In Progress in Landslide Research and Technology. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44296-4_14.

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AbstractTime prediction methods based on monitoring surface displacement (SD) are effective for early warning against shallow landslides. However, failure time prediction by Fukuzono’s original inverse-velocity (INV) method is less accurate due to variation in the inverse-velocity (1/v) caused by noise in the measured SD, which amplifies the fluctuation in the resultant 1/v. Therefore, the present study incorporates pre-analysis to acquire better prediction by reducing the effect of noise on the measured SD. The data extraction (DE) and moving average (MA) methods are used to filter the measur
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Adenuga, Olukorede Tijani, Khumbulani Mpofu, and Ragosebo Kgaugelo Modise. "Application of ARIMA-LSTM for Manufacturing Decarbonization Using 4IR Concepts." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18326-3_12.

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AbstractIncreasing climate change concerns call for the manufacturing sector to decarbonize its process by introducing a mitigation strategy. Energy efficiency concepts within the manufacturing process value chain are proportional to the emission reductions, prompting decision makers to require predictive tools to execute decarbonization solutions. Accurate forecasting requires techniques with a strong capability for predicting automotive component manufacturing energy consumption and carbon emission data. In this paper we introduce a hybrid autoregressive moving average (ARIMA)-long short-ter
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Ko’adan, Mohammed A., Mohammed A. Bamatraf, and Khalid Q. Shafal. "Clustering Analysis to Improve Web Search Ranking Using PCA and RMSE." In Advances on Smart and Soft Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6048-4_9.

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Kobialka, Hans-Ulrich. "Friction estimation – optimization of sensor configuration with respect to RMSE and costs." In Proceedings. Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-05978-1_52.

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Akanmu, Abiola, Adedeji Afolabi, and Akinwale Okunola. "Predicting Mental Workload of Using Exoskeletons for Construction Work: A Deep Learning Approach." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.69.

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Exoskeletons are gaining attention as a potential solution for addressing low back injury in the construction industry. However, use of active back-support exoskeletons in construction can trigger unintended consequences which could increase mental workload of users while working with exoskeletons. Prolonged increase in mental workload could impact workers’ wellbeing and productivity. Prediction of mental workload during exoskeleton-use could inform strategies to mitigate the triggers. This study investigates a machine-learning framework for predicting mental workload of workers while using ac
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Akanmu, Abiola, Adedeji Afolabi, and Akinwale Okunola. "Predicting Mental Workload of Using Exoskeletons for Construction Work: A Deep Learning Approach." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.69.

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Exoskeletons are gaining attention as a potential solution for addressing low back injury in the construction industry. However, use of active back-support exoskeletons in construction can trigger unintended consequences which could increase mental workload of users while working with exoskeletons. Prolonged increase in mental workload could impact workers’ wellbeing and productivity. Prediction of mental workload during exoskeleton-use could inform strategies to mitigate the triggers. This study investigates a machine-learning framework for predicting mental workload of workers while using ac
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Faiem, Nabid, Tunc Asuroglu, Koray Acici, Antti Kallonen, and Mark van Gils. "Assessment of Parkinson’s Disease Severity Using Gait Data: A Deep Learning-Based Multimodal Approach." In Communications in Computer and Information Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59091-7_3.

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AbstractThe ability to regularly assess Parkinson’s disease (PD) symptoms outside of complex laboratories supports remote monitoring and better treatment management. Multimodal sensors are beneficial for sensing different motor and non-motor symptoms, but simultaneous analysis is difficult due to complex dependencies between different modalities and their different format and data properties. Multimodal machine learning models can analyze such diverse modalities together, thereby enhancing holistic understanding of the data and overall patient state. The Unified Parkinson’s Disease Rating Scal
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Trabalhos de conferências sobre o assunto "RMSE"

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de Araujo, Juliana Tiburcio, Alexis Carbo Meseguer, and Jean-Christophe Antona. "Physics-based vs ML-based Digital Twins of Submarine Networks." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w1c.3.

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We investigate digital twin approaches to predict subsea link spectrum evolutions and QoT to facilitate spectrum sharing. We focus on a 0.5dB RMSE hybrid model with low complexity and reduced data training set.
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Chen, Tianle, Zhou Xu, Guijiang Yang, Lei Tu, Liang Wang та Ming Tang. "Enhancing φ-OFDR Sensing Distance and Accuracy based on Synchronous Equal Frequency Resampling". У Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w3g.7.

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Synchronous equal frequency resampling is proposed to simultaneously compensate both the random laser frequency sweep range and sweep nonlinearity. The strain RMSE is reduced by 16 times with sensing distance extended to 70 m.
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He, Yan, Zhiqun Zhai, Sai Chen, et al. "Transceiver Penalty and Amplifier Noise Figure Characterization for Accurate QoT Estimation in Hyperscale Disaggregated DCI Networks." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.m1j.6.

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We demonstrated that experimentally characterizing the input/frequency-dependent amplifier noise figure and input power dependent transceiver penalty can reduce the RMSE of QoT estimation from 0.662dB to 0.287dB in hyperscale disaggregated DCI production networks.
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Girard-Jollet, J., L. Shi, F. Boitier, and P. Layec. "Nonlinearity Estimation Leveraging PSD-based Monitoring and Machine Learning." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.m2e.2.

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We propose a regression model to estimate Kerr nonlinearity proportion in fiber optic transmissions. Trained on simulations and validated experimentally, the model achieves a 4% RMSE across varying power profiles, CPE parameters, and transmission reaches.
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Duan, Junyi, Jiageng Chen, Hanzhao Li, and Zuyuan He. "Convolution Network for Phase Unwrapping of Interferometric Fiber Sensing Signals." In CLEO: Applications and Technology. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_at.2024.jtu2a.207.

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A convolution neural network is proposed to reconstruct the true value from phase-wrapped interferometric sensing signals. The MAE and RMSE in a real phase dataset sampled by DAS are 0.069 p and 0.352 p respectively.
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Lan, Yang, Lixian Wang, and Zhiping Jiang. "EDFA gain profile prediction under off-target channel add/drop." In Optical Fiber Communication Conference. Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.tu2e.3.

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We propose a hybrid EDFA model to estimate gain profile under off-target channel add and drop events. Our experimental results show 0.05dB RMSE off-target prediction with on-target data only, significantly reducing sample requirements.
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Jadoon, Usman Khan, Ismael D�az, and Manuel Rodr�guez. "Comparative Assessment of Aspen Plus Modeling Strategies for Biomass Steam Co-gasification." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.124830.

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The urgent need for sustainable energy drives the exploration of biomass and plastic waste co-gasification, a promising route for producing clean fuels and chemicals, reducing greenhouse gas emissions, and minimizing fossil fuel dependence. Modeling and simulation are vital for optimizing this process, particularly syngas yield, yet comparative studies on Aspen Plus modeling techniques for steam co-gasification are limited. This research addresses this gap by comparing three Aspen Plus strategies: thermodynamic equilibrium modeling (TEM), restricted thermodynamic modeling (RTM), and kinetic mo
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Jadoon, Usman Khan, Ismael D�az, and Manuel Rodr�guez. "A Comparative Study of Aspen Plus and Machine Learning Models for Syngas Prediction in Biomass-Plastic Waste Co-gasification." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.174749.

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The co-gasification of biomass and plastic waste offers a promising pathway for sustainable syngas production, necessitating precise prediction of its composition to optimize efficiency. This study compares the performance of Aspen Plus models, including the thermodynamic equilibrium model (TEM) and restricted thermodynamic equilibrium model (RTM), with machine learning (ML) techniques, focusing on the support vector regression (SVR) for syngas prediction during steam and air co-gasification. Aspen Plus simulations provided valuable mechanistic insights, while the ML model demonstrated superio
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Mongia, Hukam C. "N+3 and N+4 Generation Aeropropulsion Engine Combustors: Part 3 — Small Engines’ Emissions and Axial Staging Combustion Technology." In ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-94572.

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Comprehensive assessment of the small rich-dome engines was conducted leading to the following emissions correlations: NOxEI LEC = 0.02991 × OPR1.9791 RMSE = 3.0% NOxEI TALON II = 0.01666 × OPR2.1403 RMSE = 2.0% NOxEI CFM TI = 0.06763 × OPR1.7458 RMSE = 2.1% NOxEI CF34 = 0.0541 × OPR1.7917R2 = 0.9794 RMSE = 2.4% NOxEI SM = 0.04782 × OPR1.8388 RMSE = 4.2% NOxEI All = 0.03856 × OPR1.9058 RMSE = 3.9% The best of the small engines’ gaseous emissions, albeit at lower takeoff pressure ratios, were shown to be very competitive with the best of medium and large size engines. Axially-staged combustion
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van Essen, Sanne, Tim Bunnik, and Jule Scharnke. "Statistical Uncertainty of Ship Response to Waves As a Function of Test Duration." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-122486.

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Abstract Wave-induced ship responses have a natural statistical variability, due to the nature of the ocean waves. This needs to be accounted for in ship design. The uncertainty and extreme values of the ship motions and loads depend on the test or simulation duration. This paper presents the experimental relation between uncertainty of root-mean-square (RMS) and most probable maximum (MPM) response values and the test duration, for a sailing ferry in steep bow-quartering waves. The RMSE uncertainty of the RMS of heave, pitch and relative wave elevation was 2–3% after 0.5 h test duration, redu
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Relatórios de organizações sobre o assunto "RMSE"

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Zeller, Lucas, Daniel McGrath, Louis Sass, Shad O’Neel, Christopher McNeil, and Emily Baker. Beyond glacier-wide mass balances : parsing seasonal elevation change into spatially resolved patterns of accumulation and ablation at Wolverine Glacier, Alaska. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48497.

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We present spatially distributed seasonal and annual surface mass balances of Wolverine Glacier, Alaska, from 2016 to 2020. Our approach accounts for the effects of ice emergence and firn compaction on surface elevation changes to resolve the spatial patterns in mass balance at 10 m scale. We present and compare three methods for estimating emergence velocities. Firn compaction was constrained by optimizing a firn model to fit three firn cores. Distributed mass balances showed good agreement with mass-balance stakes (RMSE = 0.67 m w.e., r = 0.99, n = 41) and ground-penetrating radar surveys (R
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Brodie, Katherine, Brittany Bruder, Richard Slocum, and Nicholas Spore. Simultaneous mapping of coastal topography and bathymetry from a lightweight multicamera UAS. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41440.

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A low-cost multicamera Unmanned Aircraft System (UAS) is used to simultaneously estimate open-coast topography and bathymetry from a single longitudinal coastal flight. The UAS combines nadir and oblique imagery to create a wide field of view (FOV), which enables collection of mobile, long dwell timeseries of the littoral zone suitable for structure-from motion (SfM), and wave speed inversion algorithms. Resultant digital surface models (DSMs) compare well with terrestrial topographic lidar and bathymetric survey data at Duck, NC, USA, with root-mean-square error (RMSE)/bias of 0.26/–0.05 and
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Conery, Ian, Brittany Bruder, Connor Geis, Jessamin Straub, Nicholas Spore, and Katherine Brodie. Applicability of CoastSnap, a crowd-sourced coastal monitoring approach for US Army Corps of Engineers district use. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/47568.

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This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details the pilot deployment, accuracy evaluation, and best practices of the citizen-science, coastal-image monitoring program CoastSnap. Despite the need for regular observational data, many coastlines are monitored infrequently due to cost and personnel, and this cell phone-image-based approach represents a new potential data source to districts in addition to providing an outreach opportunity for the public. Requiring minimal hardware and signage, the system is simple to install but re
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Ermolayev, Vadim, Frédéric Mallet, Vitaliy Yakovyna, et al., eds. ICTERI 2019: ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer : Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops. Kherson, Ukraine, June 12-15, 2019. CEUR Workshop Proceedings, 2019. http://dx.doi.org/10.31812/123456789/3170.

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This volume represents the proceedings of the Workshops co-located with the 15th International Conference on ICT in Education, Research, and Industrial Applications, held in Kherson, Ukraine, in June 2019. It comprises 82 contributed papers that were carefully peer-reviewed and selected from 218 submissions for the five workshops: 3L-Person, CoSinE, ITER, RMSE, and TheRMIT. The volume is structured in five parts, each presenting the contributions for a particular workshop. The topical scope of the volume is aligned with the thematic tracks of ICTERI 2019: (I) Advances in ICT Research; (II) Inf
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Fisher, Andmorgan, Taylor Hodgdon, and Michael Lewis. Time-series forecasting methods : a review. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49450.

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Time-series forecasting techniques are of fundamental importance for predicting future values by analyzing past trends. The techniques assume that future trends will be similar to historical trends. Forecasting involves using models fit on historical data to predict future values. Time-series models have wide-ranging applications, from weather forecasting to sales forecasting, and are among the most effective methods of forecasting, especially when making decisions that involve uncertainty about the future. To evaluate forecast accuracy and to compare among models fitted to a time series, thre
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Pompeu, Gustavo, and José Luiz Rossi. Real/Dollar Exchange Rate Prediction Combining Machine Learning and Fundamental Models. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004491.

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The study of the predictability of exchange rates has been a very recurring theme on the economics literature for decades, and very often is not possible to beat a random walk prediction, particularly when trying to forecast short time periods. Although there are several studies about exchange rate forecasting in general, predictions of specifically Brazilian real (BRL) to United States dollar (USD) exchange rates are very hard to find in the literature. The objective of this work is to predict the specific BRL to USD exchange rates by applying machine learning models combined with fundamental
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Pradhan, Nawa Raj. Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region, USA. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42128.

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A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km2 Reyno
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Patwa, B., P. L. St-Charles, G. Bellefleur, and B. Rousseau. Predictive models for first arrivals on seismic reflection data, Manitoba, New Brunswick, and Ontario. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329758.

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First arrivals are the primary waves picked and analyzed by seismologists to infer properties of the subsurface. Here we try to solve a problem in a small subsection of the seismic processing workflow: first break picking of seismic reflection data. We formulate this problem as an image segmentation task. Data is preprocessed, cleaned from outliers and extrapolated to make the training of deep learning models feasible. We use Fully Convolutional Networks (specifically UNets) to train initial models and explore their performance with losses, layer depths, and the number of classes. We propose t
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Konsam, Manis Kumar, Amanda Thounajam, Prasad Vaidya, Gopikrishna A, Uthej Dalavai, and Yashima Jain. Machine Learning-Enhanced Control System for Optimized Ceiling Fan and Air Conditioner Operation for Thermal Comfort. Indian Institute for Human Settlements, 2024. http://dx.doi.org/10.24943/mlcsocfacotc6.2023.

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This paper proposes and tests the implementation of a sustainable cooling approach that uses a machine learning model to predict operative temperatures, and an automated control sequence that prioritises ceiling fans over air conditioners. The robustness of the machine learning model (MLM) is tested by comparing its prediction with that of a straight-line model (SLM) using the metrics of Mean Bias Error (MBE) and Root Mean Squared Error (RMSE). This comparison is done across several rooms to see how each prediction method performs when the conditions are different from those of the original ro
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Johansen, Richard, Molly Reif, Christina Saltus, and Kaytee Pokrzywinski. A broadscale assessment of Sentinel-2 imagery and the Google Earth Engine for the nationwide mapping of chlorophyll a. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48784.

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Harmful algal blooms degrade water quality and can result in adverse health impacts to humans and wildlife. Monitoring these at scale is difficult due to the lack of coincident data. Additionally, traditional field collection methods are labor- and cost-prohibitive, resulting in disparate data collection not capable of capturing the physical and biological variations within waterbodies or regions. This research attempts to alleviate this by leveraging large, public, water quality databases coupled with open-access Google Earth Engine-derived Sentinel-2 imagery to evaluate the practical usabili
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