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Relevant bibliographies by topics / Average error percentage

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Academic literature on the topic 'Average error percentage'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 February 2022

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Journal articles on the topic "Average error percentage"

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Hayashi, Akiko, Yoshio Imai, Akira Katono, et al. "Percentage average error of tube voltage and X-ray output." Japanese Journal of Radiological Technology 51, no. 8 (1995): 1158. http://dx.doi.org/10.6009/jjrt.kj00001352733.

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Manik, Simson, Abdul Muis Muslimin, and Aries A. Subgan. "PERANCANGAN ALAT UKUR INTENSITAS CAHAYA BERBASIS ARDUINO LEONARDO MENGGUNAKAN SENSOR LDR (Light Dependent Resistor)." Jurnal Natural 16, no. 1 (2020): 1–13. http://dx.doi.org/10.30862/jn.v16i1.46.

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Lux meter is a device used to measure the intensity of light in an area. The purpose of this thesis is to design a light intensity measuring device using LDR components as a light sensor, comparing light intensity measuring devices made using LDR sensors and Arduino Leonardo based microcontrollers with standard tools. The data used in this study are primary data. The data obtained is then processed using MS. Excel. The type of light bulbs used are Philips CFL (Philips Essential) lamps, each lamp having a power of 5, 8, 11, 14, 18, 23, 27, 32, 35, and 50 watts with a luxmeter vertical distance

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Johnstone, Dylan, Krista Nordback, and Sirisha Kothuri. "Annual Average Nonmotorized Traffic Estimates from Manual Counts: Quantifying Error." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 43 (2018): 134–44. http://dx.doi.org/10.1177/0361198118792338.

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Across the United States, jurisdictions are investing more in bicycle and pedestrian infrastructure, which can benefit from nonmotorized traffic volume data. The design of nonmotorized counting programs varies. Whereas some agencies use automated counters to collect continuous and short duration counts, the most common type of bicycle and pedestrian counting is manual counting either in the field or from video. The objective of this research is to identify the optimal times of day to conduct manual counts for the purposes of accurately estimating annual average daily nonmotorized traffic (AADN

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Putro, Mohamad Tri Azis Budi Cahyono. "IMPLEMENTATION OF DISTRIBUTED AVERAGE CONSENSUS METHOD ON WIRELESS SENSOR NETWORK FOR MONITORING TEMPERATURE AND HUMIDITY IN SWITCHGEAR ROOM." INAJEEE Indonesian Journal of Electrical and Eletronics Engineering 4, no. 1 (2021): 12. http://dx.doi.org/10.26740/inajeee.v4n1.p12-15.

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The development of wireless sensor networks is currently very rapid in various sectors. One of the implementations of the wireless sensor network is for monitoring temperature and humidity. In monitoring a room or a large area, many nodes are installed at a certain point. With the number of senses by each node so that one data that can represent the area is needed. To get one data that can represent the data in that area, we need a consensus method. In this study, the average distributed consensus method was used to obtain data representation from an area's wireless sensor network. After testi

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Prapcoyo, Hari. "PERAMALAN JUMLAH MAHASISWA MENGGUNAKAN MOVING AVERAGE." Telematika 15, no. 1 (2018): 67. http://dx.doi.org/10.31315/telematika.v15i1.3069.

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AbstractThe Process of using resources in higher education is influenced by the up and down of the number students. The purpose of this study is to predict the number of students who study in the department of informatics engineering UPN Veteran Yogyakarta for the next periods. This research, data is taken from forlap dikti for Informatics Engineering fom 2009 until 2016 at UPN Veteran Yogyakarta. The method that used to forecast the number of students is a Moving Average method consisting of: Single Moving Average (SMA), Weighted Moving Average (WMA) and Exponential Moving Average (EMA). This

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Watson, Linda, Siwei Qi, Andrea Deiure, et al. "Predicting symptom complexity: Using autoregressive integrated moving average (ARIMA) models to create responsive clinic scheduling." Journal of Clinical Oncology 39, no. 15_suppl (2021): e13529-e13529. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e13529.

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e13529 Background: Increasing cancer incidence, coupled with a trend in treating patients for longer periods of time, presents challenges in addressing all patients’ symptoms/concerns within the allotted time for ambulatory clinic appointments. Consequently, the ability to forecast and monitor the percentage of cancer patients with different symptom complexity levels is extremely valuable. Symptom complexity is a summary score that weighs the severity of all patient reported symptom scores at one time point. If a clinic could predict how many patients may need more time due to complex symptom

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Pathak, Sunil, and Neelesh Kumar Jain. "Performance of pulsed-electrochemical honing and pulsed-electrochemical finishing in improving quality of bevel gears." Manufacturing Review 5 (2018): 14. http://dx.doi.org/10.1051/mfreview/2018012.

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This article presents a comparative study concerning performance of pulsed-electrochemical honing (PECH) and pulsed-electrochemical finishing (PECF) in straight bevel gear finishing. Performance of these processes were compared in terms of average percentage difference in the considered parameters of surface features of bevel gear namely average percentage differences in average surface roughness ‘PDRa’, maximum surface roughness ‘PDRmax’ and depth of surface roughness ‘PDRz’, micro-geometry (i.e. average percentage differences in single pitch error ‘PDfp’, adjacent pitch error ‘PDfu’, cumulat

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Alam, S. M. Mahfuz, and Mohd Hasan Ali. "Equation Based New Methods for Residential Load Forecasting." Energies 13, no. 23 (2020): 6378. http://dx.doi.org/10.3390/en13236378.

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This work proposes two non-linear and one linear equation-based system for residential load forecasting considering heating degree days, cooling degree days, occupancy, and day type, which are applicable to any residential building with small sets of smart meter data. The coefficients of the proposed nonlinear and linear equations are tuned by particle swarm optimization (PSO) and the multiple linear regression method, respectively. For the purpose of comparison, a subtractive clustering based adaptive neuro fuzzy inference system (ANFIS), random forests, gradient boosting trees, and long-term

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Utomo, A. P., K. Yuana, E. Narulita, K. Fikri, and B. Wahono. "Students’ Errors in Solving Science Reasoning-Domain of Trends in International Mathematics and Science Study (TIMSS)." Jurnal Pendidikan IPA Indonesia 7, no. 1 (2018): 48–53. http://dx.doi.org/10.15294/jpii.v7i1.11352.

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This research aims to identify the errors of students’ answers in solving the TIMSS cognitive domain of reasoning. This research was a qualitative descriptive research. A total 259 students from four secondary schools located in rural and urban areas in Jember, East Java participated in a paper and pencil test. Error identification was examined by reducing the result of wrong students’ answer and grouping based on error type of general errors. The results showed that the average percentage of total errors from the four schools were contradicting error of 7.3%, disregarding evidence error of 5.

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Sumari, Arwin Datumaya Wahyudi, Dimas Rossiawan Hendra Putra, Muhammad Bisri Musthofa, and Ngat Mari. "Pandemic dynamics prediction in Java using the Moving Average method and the Knowledge Growing System (KGS)." Jurnal Teknologi dan Sistem Komputer 9, no. 1 (2020): 31–40. http://dx.doi.org/10.14710/jtsiskom.2020.13779.

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This study aims to analyze the comparative performance of pandemic dynamics prediction methods on the island of Java, based on data from March to May 2020 covering the provinces of DKI Jakarta, West Java, Central Java, DI Yogyakarta, and East Java. The prediction uses Knowledge Growing System (KGS) and time series models, namely Single Moving Average (SMA) and Exponential Moving Average (EMA). Based on the Mean Absolute Percentage Error (MAPE) computational results, the EMA method produces a lower error rate than the SMA method with 47.94 % on average. The KGS prediction with a Degree of Certa

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Dissertations / Theses on the topic "Average error percentage"

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Venkataraman, Mahalingam. "Improving accuracy in logarithmic multiplication using operand decomposition." [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001140.

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Book chapters on the topic "Average error percentage"

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Abeyrathna, Kuruge Darshana, and Chawalit Jeenanunta. "Hybrid Particle Swarm Optimization With Genetic Algorithm to Train Artificial Neural Networks for Short-Term Load Forecasting." In Research Anthology on Artificial Neural Network Applications. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch010.

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This research proposes a new training algorithm for artificial neural networks (ANNs) to improve the short-term load forecasting (STLF) performance. The proposed algorithm overcomes the so-called training issue in ANNs, where it traps in local minima, by applying genetic algorithm operations in particle swarm optimization when it converges to local minima. The training ability of the hybridized training algorithm is evaluated using load data gathered by Electricity Generating Authority of Thailand. The ANN is trained using the new training algorithm with one-year data to forecast equal 48 periods of each day in 2013. During the testing phase, a mean absolute percentage error (MAPE) is used to evaluate performance of the hybridized training algorithm and compare them with MAPEs from Backpropagation, GA, and PSO. Yearly average MAPE and the average MAPEs for weekdays, Mondays, weekends, Holidays, and Bridging holidays show that PSO+GA algorithm outperforms other training algorithms for STLF.

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Bao, Qiong, Bruno Kochan, Tom Bellemans, Davy Janssens, and Geert Wets. "Activity-Based Travel Demand Forecasting Using Micro-Simulation." In Data Science and Simulation in Transportation Research. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4920-0.ch009.

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Activity-based models of travel demand employ in most cases a micro-simulation approach, thereby inevitably including a stochastic error that is caused by the statistical distributions of random components. As a result, running a transport micro-simulation model several times with the same input will generate different outputs. In order to take the variation of outputs in each model run into account, a common approach is to run the model multiple times and to use the average value of the results. The question then becomes: What is the minimum number of model runs required to reach a stable result? In this chapter, systematic experiments are carried out by using the FEATHERS, an activity-based micro-simulation modeling framework currently implemented for Flanders (Belgium). Six levels of geographic detail are taken into account, which are building block level, subzone level, zone level, superzone level, province level, and the whole Flanders. Three travel indices (i.e., the average daily number of activities per person, the average daily number of trips per person, and the average daily distance travelled per person), as well as their corresponding segmentations with respect to socio-demographic variables, transport mode alternatives, and activity types are calculated by running the model 100 times. The results show that application of the FEATHERS at a highly aggregated level only requires limited model runs. However, when a more disaggregated level is considered (the degree of the aggregation here not only refers to the size of the geographical scale, but also to the detailed extent of the index), a larger number of model runs is needed to ensure confidence of a certain percentile of zones at this level to be stable. The values listed in this chapter can be consulted as a reference for those who plan to use the FEATHERS framework, while for the other activity-based models the methodology proposed in this chapter can be repeated.

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Conant, James K., and Peter J. Balint. "The Future of the Council on Environmental Quality and the Environmental Protection Agency: 2015–2035." In The Life Cycles of the Council on Environmental Quality and the Environmental Protection Agency. Oxford University Press, 2016. http://dx.doi.org/10.1093/oso/9780190203702.003.0010.

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In this chapter, we consider possible futures for the Council on Environmental Quality (CEQ) and the Environmental Protection Agency (EPA) under several scenarios. Before beginning, we offer some caveats and disclaimers. “Prediction is very difficult, especially about the future.” This quotation—often credited to physicist Niels Bohr—captures the dilemma of prediction by stating it as a truism. Statistician Nate Silver, who won fame for accurately forecasting the 2008 and 2012 U.S. presidential elections, argues that in general the record of prognostication in public affairs, the field encompassing the ideas in this book, is particularly poor. For example, in the late 1980s few specialists predicted the collapse of the Soviet Union, an event of enormous scale and importance that appears in hindsight to have been imminent and inevitable. More recently on the domestic front political experts generally failed to foresee the rise of the Tea Party, which has roiled the last three American electoral cycles and generated a significant rightward pull on the Republican Party and on U.S. politics more broadly. Psychologist Phillip Tetlock, who examined the record of expert predictions in the arena of public affairs, reports poor results. In his research he found that “expertise . . . had no across-the-board effect on forecasting accuracy.” He observed that egregious prediction errors are surprisingly common, even among experts whose prediction skills are otherwise rated as better than average. About 10 percent of the time events actually occurred that these higher-performing experts had estimated to be impossible, while about 20 percent of the time events failed to occur that these experts had estimated to be sure things. The results were 10 percentage points worse in both directions for the poorer-performing experts in Tetlock’s studies. Given these findings, the predictive limitations of the agency life cycle models we consider in this book are not surprising.

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Conference papers on the topic "Average error percentage"

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Chaves, Gabriela, Hamidreza Karami, Danielle Monteiro, and Virgilio José Martins Ferreira. "Development of a Virtual Flowmeter as an Enhanced Alternative for Field Production Monitoring." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206259-ms.

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Abstract Flowrate is a valuable information for the oil and gas industry. High accuracy on flowrate estimation enhances production operations to control and manage the production. Recognized as a cost-efficient solution, the VFM (virtual flowmeter) is a mathematical-based technology designed to estimate the flowrates using available field instrumentation. The VFM approach developed in this work combines black-box simulations with mixed-integer linear programming (MILP) problem to obtain the flowrates dismissing the tuning process. The methodology included a set of multiphase flow correlations,

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Posada, Catalina, and Paulo Waltrich. "Performance of Two-Phase Flow Models on the Prediction of Oscillatory Flow Conditions." In ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/omae2016-54954.

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The present investigation presents a comparative study between two-phase flow models and experimental data. Experimental data was obtained using a 42 m long, 0.05 m ID tube system. The experimental data include conditions for pressures ranging from 1.2 to 2.8 bara, superficial liquid velocities 0.02–0.3 m/s, and superficial gas velocity ranges 0.17–26 m/s. The experimental data was used to evaluate the performance of steady-state empirical and mechanistic models while estimating liquid holdup and pressure gradient under steady-state and oscillatory conditions. The purpose of this analysis is f

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Yong, Sihan, Zhuoyuan Zheng, Pingfeng Wang, and Yumeng Li. "Machine Learning Assisted Design for Active Cathode Materials." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23963.

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Abstract The traditional way of designing materials, including experimental measurement and computational simulation, are not efficient. Machine learning is considered a promising solution for material design in the recent years. By observing from previous data, machine learning finds patterns, learns from the patterns and predict the material properties. In this study, machine learning methods are used for discovering new cathode with better properties, includes crystal system learning and the property prediction. K-Folder cross-validation is used for finding the best training data with a lim

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Bielecki, Mark F., Jason J. Kemper, and Thomas L. Acker. "A Methodology for Comprehensive Characterization of Errors in Wind Power Forecasting." In ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90381.

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Wind power forecasting will play a more important role in electrical system planning with the greater wind penetrations of the coming decades. Wind will most likely comprise a larger percentage of the generation mix, and as a result forecasting errors may have more significant effects on balancing operations. The natural uncertainties associated with wind along with limitations in numerical weather prediction (NWP) models lead to these forecasting errors, which play a considerable role in the impacts and costs of utility-scale wind integration. The premise of this project was to examine errors

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Hu, Yuh-Chung, Wei-Hsin Gau, and Wei-Hsiang Tu. "High Precision Young’s Modulus Extraction of Thin Films Through Measuring the Electric-Circuit Behavior of Microstructures." In ASME 2005 Pacific Rim Technical Conference and Exhibition on Integration and Packaging of MEMS, NEMS, and Electronic Systems collocated with the ASME 2005 Heat Transfer Summer Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/ipack2005-73337.

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This paper is aimed at developing a high precision algorithm for extracting the Young’s modulus of thin films through the capacitance-voltage measurement of microstructures at wafer level. Two flat micro cantilever beams made of single crystalline silicon are demonstrated. The average value of extracted Young’s modulus in (110) crystalline plane by the present methodology is about 169 GPa, compared to the well-defined value of 168 GPa, the error percentage is within 1% and the high precision and repeatability of the present methodology are verified. Since the driving and measuring signals of t

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Lall, Pradeep, Rahul Vaidya, Vikrant More, and Kai Goebel. "Prognostic Health Monitoring of Damage Progression in Leadfree Electronics Under Sequential Exposure to Thermal Aging and Thermal Cycling." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-40668.

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Deployed electronic systems may be subjected to cyclic thermo-mechanical loads during storage and subsequent to deployment. Aging has been previously shown to affect the reliability and constitutive behavior of second-level leadfree interconnects. Prognostication of accrued damage and assessment of residual life is extremely critical for ultra-high reliability systems in which the cost of failure is too high. The presented methodology uses leading indicators of failure based on micro-structural evolution of damage to identify impending failure in electronic systems subjected to sequential stre

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Yang, Xue, Rajan Borse, and Nader Satvat. "MOCUM Code Verification and Sensibility Study Using C5G7 Benchmark." In 2016 24th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/icone24-60443.

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This work uses the 2-D C5G7 benchmark to verify the accuracy of the MOCUM code, a parallel neutronics program based on the method of characteristics (MOC) for solving arbitrary core geometry. Compared to the MCNP results, MOCUM k-eff, maximum assembly and pin power percentage errors are 0.02%, −0.06%, and 0.64%, respectively. The results demonstrate the high accuracy of the MOCUM code. The calculation uses a total of 56 threads, and the runtime on dual Intel Xeon E5-2699 v3 CPUs is 26 minutes, with speed up higher than 50 times. The sensitivity study of various MOC parameters using the calcula

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Effiong, Augustine James, Joseph Okon Etim, and Anietie Ndarake Okon. "Artificial Intelligence Model for Predicting Formation Damage in Oil and Gas Wells." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/207129-ms.

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Abstract An artificial neural network (ANN) was developed to predict skin, a formation damage parameter in oil and gas drilling, well completion and production operations. Four performance metrics: goodness of fit (R2), mean square error (MSE), root mean square error (RMSE), average absolute percentage relative error (AAPRE), was used to check the performance of the developed model. The results obtained indicate that the model had an overall MSE of 355.343, RMSE of 18.850, AAPRE of 4.090 and an R2 of 0.9978. All the predictions agreed with the measured result. The generalization capacity of th

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Wang, Xinjun, Gaoliang Liao, Ding Zhu, Jinling Yao, and Xiaowei Bai. "Study on the Sampling Quality of Wetness Measurement Probe for Thermodynamic Methods." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68262.

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Software FLUENT was applied to conduct the numerical calculations of the sampling velocity at the sampling nozzle inlet of the wetness measurement probe and the trajectories of water droplets in the steam flow. The steam wetness of samples and the percentage of the droplets with different diameters entering the sampling nozzle were ascertained. The results showed that wetness measurement probe affected the flow of vapor phase at some degrees. Especially, there was a deflection of stream line nearby the sampling nozzle. It was showed that the isokinetic sampling could not be accomplished becaus

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Bashash, Saeid, Kushan Vora, Nader Jalili, Philip G. Evans, Marcelo J. Dapino, and Julie Slaughter. "Modeling Major and Minor Hysteresis Loops in Galfenol-Driven Micro-Positioning Actuators Using a Memory-Based Hysteresis Framework." In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2271.

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This article presents a memory-based hysteresis modeling framework which uses a mathematical mapping technique for accurate prediction of major and minor hysteresis loops in Galfenol-driven actuators. The model is based on three properties of hysteretic materials which have been recently established for piezoelectric actuators. These properties are: targeting of turning points, curve alignment and the wiping-out effect. To describe the anhysteretic behavior of the actuator, we initially separate the nonlinearity of the hysteretic response from the hysteresis looping effect and approximate it w

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