69 results for “root mean square”

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Research ArticleOpen accessIn the abstractAnalysis of Artificial Neural Network Point Forecasting Models and Prediction Intervals for Solar Irradiance EstimationAntônio Fabrício Guimarães de Sousa, Helaine Cristina Moraes Furtado, Wilson Negrão Macêdo, Anderson Alvarenga de Moura MenesesAn accurate knowledge on solar irradiance prediction is particularly required for proper development and planning of Photovoltaic (PV) energy systems. The main purpose of the present research is to assess the accuracy of Artificial Neural Networks (ANN) short-term forecast of univariate solar irradiance time series, with conventional point prediction and Prediction Intervals (PIs), comparing models. The Lower Upper Bound Estimation … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 17 Jul 2020 · 7,443 accessesView PDF Cite

Research ArticleOpen accessIn the abstractNondestructive Assessment of Egg Freshness using a Synchronous Fluorescence Spectral TechniqueJianhu Wu, Guifeng Li, Yankun Peng et al.Freshness is an important index of egg quality. In this study, a synchronous fluorescence spectral technique was employed to determine the freshness of an intact egg. Synchronous fluorescence spectra of intact eggs were acquired using a fluorescence spectrometer supported by a laboratory fluorescence acquisition device and egg freshness (Haugh Unit) was obtained using destructive methods. Eggs feature fluorescence signals were … …American Journal of Biochemistry and Biotechnology, Vol. 15, Issue 4 · 19 Dec 2019 · 8,135 accessesView PDF Cite

Research ArticleOpen accessIn the abstractComparison of Linear and Non-Linear Regression Models for Non-Invasive Blood Glucose MeasurementDorsaf Ghozzi, Yassine Manai, Khaled NouriThis paper deals with a new approach of non-invasive glucose monitoring based on near infrared spectroscopy. The proposed approach is coupled with a regression analysis in order to improve the predictive capacity of the designed device. Basic spectral data is a comparison that has been established between linear and non-linear machine learning regression algorithms. The experimental results show that feed … …Journal of Computer Science, Vol. 15, Issue 11 · 13 Nov 2019 · 7,869 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMapping of Temperature Trend Slope in Iran′s Zayanderud River Basin: A Comparison of Interpolation MethodsAli Zahraei, Saeid Eslamian, Ali Saeidi Rizi et al.The spatial distribution of daily, nightly and mean temperature trend in Iran′s Zayanderud river basin was carried out in this study by applying three approaches of interpolation including Inverse Distance Weighting (IDW), Multiple Linear Regression (MLR) and integration of these two methods (IDW+MLR). In this paper, t-test and statistical measures including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 2 · 26 Jun 2019 · 7,479 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPerformance Comparison of Passive Fault Tolerant Control Strategy with PI and Fuzzy Control of Single-Tank Level Process with Sensor and System FaultHimanshukumar R. Patel, Vipul A. ShahFault-Tolerant Control (FTC) strategy has gain maximum attention in recent years in chemical industries due to economical and safety hazards perspective. Targeting at the decreasing control performance of the single-tank level control process under the constraint of system and sensor faults, this article presents model-based Passive Fault-Tolerant Control (PFTC) strategy which are based on conventional and artificial intelligence control. The … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 2 · 24 Jun 2019 · 7,606 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEstimation of Soils Electrical Resistivity using Artificial Neural Network ApproachKpomonè Komla Apaloo-Bara, Adekunlé Akim Salami, Mawugno Koffi Kodjo et al.The knowledge of the ground electrical resistivity is essential to ensure the protection of electrical and telecommunications networks. However, the monitoring of its values is an expensive task which takes long time. Therefore, its prediction is important. This study investigates on predicting soil electrical resistivity using Artificial Neural Networks. Nine sites of our city (Lome, TOGO) were considered. After characterization … …American Journal of Applied Sciences, Vol. 16, Issue 2 · 13 Mar 2019 · 9,522 accessesView PDF Cite

Research ArticleOpen accessIn the abstractForecasting Ozone Concentrations Using Box-Jenkins ARIMA Modeling in MalaysiaWan Rozita Wan Mahiyuddin, Nur Izzah Jamil, Zamtira Seman et al.Time series analysis and forecasting has become a major tool in many applications in air pollution and environmental management fields. Among the most effective approaches for analyzing time series data is the model introduced by Box and Jenkins. In this study, we used Box-Jenkins methodology to build Autoregressive Integrated Moving Average (ARIMA) model on the average of monthly ozone data … …American Journal of Environmental Sciences, Vol. 14, Issue 3 · 25 May 2018 · 8,946 accessesView PDF Cite

Research ArticleOpen accessIn the abstractApplication of Time Series Modeling to Study River Water QualityMaryam Ghashghaie, Kaveh Ostad-Ali-Askari, Saeid Eslamian, Vijay P. SinghWater deficit problem originates from two factors: population increase and water pollution. However, studying and forecasting the quality of water are necessary to avoid serious problems in future through managerial works. In present study, using time series modeling, the quality of Madian Rood River is studied at Baraftab station using time series analysis. Nine parameters of water quality are studied … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 2 · 25 Apr 2018 · 8,938 accessesView PDF Cite

Research ArticleOpen accessIn the abstractConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,736 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEstimating the Scouring Depth of Bridge Pier Using Self-Organizing Neural Networks (SOM)Abolfazl Rafat, Gholam Abbas Barani, Amineh NaseriScouring is caused as a result of erosion of river bed by water flow and materials carried by water. This research estimates the scouring depth using self-organizing neural network (SOM). The obtained findings were compared with findings of other models. It was found that self- organizing neural network (SOM) has higher correlation coefficient (0.98), compared to other methods. It was … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 4 · 27 Nov 2017 · 7,512 accessesView PDF Cite