Relevant bibliographies by topics / Prediction of Accuracy result

Contents

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

Academic literature on the topic 'Prediction of Accuracy result'

Author: Grafiati
Published: 5 June 2025
Last updated: 1 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Prediction of Accuracy result.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Prediction of Accuracy result"

1

Harahap, Rahma Sari, Iskandar Muda, and Rina Br Bukit. "Analisis penggunaan metode Altman Z-Score dan Springate untuk mengetahui potensi terjadinya Financial Distress pada perusahaan manufaktur sektor industri dasar dan kimia Sub Sektor semen yang terdaftar di Bursa Efek Indonesia 2000-2020." Owner 6, no. 4 (2022): 4315–25. http://dx.doi.org/10.33395/owner.v6i4.1576.

Full text
Abstract:
The objective of the research is to find out the result of predicting bankruptcy, using Altman Z-Score and Springate methods in the manufacturing companies of basic industrial and chemistry sectors, cement sub-sector listed on BEI (Indonesia Stock Exchange) in the period of 2000-2020 and to determine the most accurate predicting method of bankruptcy to be applied in the manufacturing companies in basic industrial and chemistry sectors, cement sub-sector. The research employs descriptive quantitative method. The samples are taken by using purposive sampling method with three manufacture compani
APA, Harvard, Vancouver, ISO, and other styles
2

TJ, Mr GOWTHAM. "ELECTION RESULT PREDICTION." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem36223.

Full text
Abstract:
This study utilizes Text Blob for sentiment analysis of social media and news data to predict election results. By analyzing sentiment polarity, a comprehensive understanding of public opinion towards political entities is obtained. Machine learning algorithms are employed to build predictive models using historical election data. Results demonstrate the effectiveness of sentiment analysis in enhancing prediction accuracy compared to traditional methods. This research has implications for political campaigns and policymakers in gauging public sentiment and anticipating electoral outcomes. Keyw
APA, Harvard, Vancouver, ISO, and other styles
3

Fang, Yiheng. "Prediction of the Ammonia Nitrogen Content with Improved Grey Model by Markov Chain." Highlights in Science, Engineering and Technology 88 (March 29, 2024): 156–61. http://dx.doi.org/10.54097/zee1cd17.

Full text
Abstract:
Water pollution prediction plays a crucial role in environmental protection and sustainable development. This study proposes an innovative approach to enhance the accuracy of water pollution prediction by combining the grey prediction model (GM) with Markov chain analysis. This research focuses on predicting the concentration of ammonia nitrogen (NH3-N) in Dongting Lake, a significant water body. Grey prediction models (GM) are utilized to forecast NH3-N content, addressing the challenge posed by incomplete or insufficient data. However, due to the dynamic nature of water quality indicators, G
APA, Harvard, Vancouver, ISO, and other styles
4

Yolanda, Anggie. "Prediksi Pergerakan Harga Saham Menggunakan Support Vector Machines Di Indonesia." BUDGETING : Journal of Business, Management and Accounting 5, no. 2 (2024): 1175–88. http://dx.doi.org/10.31539/budgeting.v5i2.9829.

Full text
Abstract:
Predicting stock movements is challenging due to their dynamic nature and influence from various factors. One of these factors is the lack of research considering the use of fundamental analysis regarding currency exchange rates and the use of foreign stock index movements related to technical analysis. This research aims to predict stock price movements in Indonesia based on sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machine. The results obtained have an average prediction accuracy rate of 65.33%. The inclusion of currency exchange rates and foreign
APA, Harvard, Vancouver, ISO, and other styles
5

Assrani, Dwika, Pahala Sirait, and Andri Andri. "Pembobotan Kriteria Dalam Prediksi Meningitis Tuberkulosis Menggunakan Metode SWARA dan Nearest Neighbor." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 4 (2021): 1453. http://dx.doi.org/10.30865/mib.v5i4.3276.

Full text
Abstract:
Weights greatly affect the value and results of decisions or predictions of a test data, a problem that often occurs in the results of the prediction process is the weighting of symptom attributes which is less certain of the value of the weight, thus affecting the prediction results and the level of accuracy of a prediction itself. This study predicts a data using the Nearest Neighbor method where in the process of predicting the attribute weight value does not yet have a definite value for testing. Then we need an attribute weighting for each test attribute to get a definite weight value res
APA, Harvard, Vancouver, ISO, and other styles
6

Wilson, Stewart W. "Classifier Fitness Based on Accuracy." Evolutionary Computation 3, no. 2 (1995): 149–75. http://dx.doi.org/10.1162/evco.1995.3.2.149.

Full text
Abstract:
In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier's fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier's fitness is given by a measure of the prediction's accuracy. The system executes the genetic algorithm in niches defined by the match sets, instead of panmictically. These aspects of XCS result in its population tending to form a complete and accurate mapping X × A → P from inputs and actions to payoff predict
APA, Harvard, Vancouver, ISO, and other styles
7

Tong, Tingting, and Zhen Li. "Predicting learning achievement using ensemble learning with result explanation." PLOS ONE 20, no. 1 (2025): e0312124. https://doi.org/10.1371/journal.pone.0312124.

Full text
Abstract:
Predicting learning achievement is a crucial strategy to address high dropout rates. However, existing prediction models often exhibit biases, limiting their accuracy. Moreover, the lack of interpretability in current machine learning methods restricts their practical application in education. To overcome these challenges, this research combines the strengths of various machine learning algorithms to design a robust model that performs well across multiple metrics, and uses interpretability analysis to elucidate the prediction results. This study introduces a predictive framework for learning
APA, Harvard, Vancouver, ISO, and other styles
8

Liu, Keqian, Ang Li, Xinran Lin, Zhuobin Mao, and Weiyang Zhang. "Empirical study on the performance of various machine learning models in predicting stock price movements as a binary classification task." Applied and Computational Engineering 55, no. 1 (2024): 129–44. http://dx.doi.org/10.54254/2755-2721/55/20241403.

Full text
Abstract:
This paper examines the accuracy of stock price rise-or-fall predictions of seven different machine learning algorithms, including support vector machines and random forests, for three industry types: securities, banks, and Internet companies. The purpose of the research is to explore the effects of different models in the stock market, so as to help people choose the optimal machine learning model in predicting different types of stocks. The study produced nine features based on the study by Patel et al for prediction. By collecting 9 types of stock data from companies in different industries
APA, Harvard, Vancouver, ISO, and other styles
9

Alamer, Latifah. "Intelligent Health Risk and Disease Prediction Using Optimized Naive Bayes Classifier." Journal of Internet Services and Information Security 13, no. 1 (2023): 01–10. http://dx.doi.org/10.58346/jisis.2023.i1.001.

Full text
Abstract:
Machine learning is the subset of Artificial Intelligence and it is used for prediction various real time data analytics applications. Health care monitoring is the major area to analyse the result and make effective decisions. We need intelligent and automated process for predicting diseases using medical dataset. Machine learning methods are proposed to handle the dataset. Smart healthcare prediction is proposed to identify the user or patient information or symptoms as an input. Our system has forecasting accuracy index based on likelihood of the disease and health information. We use Naive
APA, Harvard, Vancouver, ISO, and other styles
10

Fauser, Daniel V., and Andreas Gruener. "Corporate Social Irresponsibility and Credit Risk Prediction: A Machine Learning Approach." Credit and Capital Markets – Kredit und Kapital: Volume 53, Issue 4 53, no. 4 (2020): 513–54. http://dx.doi.org/10.3790/ccm.53.4.513.

Full text
Abstract:
This paper examines the prediction accuracy of various machine learning (ML) algorithms for firm credit risk. It marks the first attempt to leverage data on corporate social irresponsibility (CSI) to better predict credit risk in an ML context. Even though the literature on default and credit risk is vast, the potential explanatory power of CSI for firm credit risk prediction remains unexplored. Previous research has shown that CSI may jeopardize firm survival and thus potentially comes into play in predicting credit risk. We find that prediction accuracy varies considerably between algorithms
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Prediction of Accuracy result"

1

Johansson, Filip, and Jesper Wikström. "Result Prediction by Mining Replays in Dota 2." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2288.

Full text
Abstract:
Context: Real-time games like Dota 2 lack the extensive mathematical modeling of turn-based games that can be used to make objective statements about how to best play them. Understanding a real-time computer game through the same kind of modeling as a turn-based game is practically impossible. Objectives: In this thesis an attempt was made to create a model using machine learning that can predict the winning team of a Dota 2 game given partial data collected as the game progressed. A couple of different classifiers were tested, out of these Random Forest was chosen to be studied more in depth.
APA, Harvard, Vancouver, ISO, and other styles
2

GAO, HONGLIANG. "IMPROVING BRANCH PREDICTION ACCURACY VIA EFFECTIVE SOURCE INFORMATION AND PREDICTION ALGORITHMS." Doctoral diss., University of Central Florida, 2008. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3286.

Full text
Abstract:
Modern superscalar processors rely on branch predictors to sustain a high instruction fetch throughput. Given the trend of deep pipelines and large instruction windows, a branch misprediction will incur a large performance penalty and result in a significant amount of energy wasted by the instructions along wrong paths. With their critical role in high performance processors, there has been extensive research on branch predictors to improve the prediction accuracy. Conceptually a dynamic branch prediction scheme includes three major components: a source, an information processor, and a predict
APA, Harvard, Vancouver, ISO, and other styles
3

Vasudev, R. Sashin, and Ashok Reddy Vanga. "Accuracy of Software Reliability Prediction from Different Approaches." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-1298.

Full text
Abstract:
Many models have been proposed for software reliability prediction, but none of these models could capture a necessary amount of software characteristic. We have proposed a mixed approach using both analytical and data driven models for finding the accuracy in reliability prediction involving case study. This report includes qualitative research strategy. Data is collected from the case study conducted on three different companies. Based on the case study an analysis will be made on the approaches used by the companies and also by using some other data related to the organizations Software Qua
APA, Harvard, Vancouver, ISO, and other styles
4

Groppe, Matthias. "Influences on aircraft target off-block time prediction accuracy." Thesis, Cranfield University, 2011. http://dspace.lib.cranfield.ac.uk/handle/1826/7277.

Full text
Abstract:
With Airport Collaborative Decision Making (A-CDM) as a generic concept of working together of all airport partners, the main aim of this research project was to increase the understanding of the Influences on the Target Off-Block Time (TOBT) Prediction Accuracy during A-CDM. Predicting the TOBT accurately is important, because all airport partners use it as a reference time for the departure of the flights after the aircraft turn-round. Understanding such influencing factors is therefore not only required for finding measures to counteract inaccurate TOBT predictions, but also for establishin
APA, Harvard, Vancouver, ISO, and other styles
5

Ilska, Joanna Jadwiga. "Understanding genomic prediction in chickens." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/15876.

Full text
Abstract:
Genomic prediction (GP) is a novel tool used for prediction of EBVs by using molecular markers. Within the last decade, GP has been widely introduced into routine evaluations of cattle, pig and sheep populations, however, its application in poultry has been somewhat delayed, and studies published to date have been limited in terms of population size and marker densities. This study shows a thorough evaluation of the benefits that GP could bring into routine evaluations of broiler chickens, with particular attention given to the accuracy and bias of Genomic BLUP (GBLUP) predictions. The data us
APA, Harvard, Vancouver, ISO, and other styles
6

Govender, Evandarin. "An intelligent deflection prediction system for machining of flexible components." Thesis, Nottingham Trent University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367158.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Leguerrier, Alexandra R. "Investigating Differences in Reaction Time and Preparatory Activation as a Result of Varying Accuracy Requirements." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38410.

Full text
Abstract:
The preparation and initiation of movement has previously been described using a neural accumulation model; this model involves an increase of neural activation in the motor cortex (M1) from baseline to a subthreshold level following a warning signal, which is maintained until presentation of an imperative stimulus (IS). Activity then increases until reaching movement initiation threshold. This model predicts that variability in activation during preparation may influence reaction time (RT) and its variability. The purpose of this thesis project was to determine whether differences in RT/varia
APA, Harvard, Vancouver, ISO, and other styles
8

Salam, Patrous Ziad, and Safir Najafi. "Evaluating Prediction Accuracy for Collaborative Filtering Algorithms in Recommender Systems." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186456.

Full text
Abstract:
Recommender systems are a relatively new technology that is commonly used by e-commerce websites and streaming services among others, to predict user opinion about products. This report studies two specific recommender algorithms, namely FunkSVD, a matrix factorization algorithm and Item-based collaborative filtering, which utilizes item similarity. This study aims to compare the prediction accuracy of the algorithms when ran on a small and a large dataset. By performing cross-validation on the algorithms, this paper seeks to obtain data that supposedly may clarify ambiguities regarding the ac
APA, Harvard, Vancouver, ISO, and other styles
9

Schellekens, Fons Jozef. "Fundamentals, accuracy and input parameters of frost heave prediction models." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ26887.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Norberg, Sven. "Prediction of the fatigue limit : accuracy of post-processing methods." Licentiate thesis, Stockholm, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4061.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Prediction of Accuracy result"

1

University of Texas at Austin. Construction Industry Institute. Improving Early Estimates Research Team., ed. Quantitative prediction of estimate accuracy. Construction Industry Institute, University of Texas at Austin, 1999.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Saleh, Muftah A. Distillation clear liquid and froth height prediction accuracy. UMIST, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Rauscher, Harold M. The microcomputer scientific software series 4: Testing prediction accuracy. U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Moses, O. Douglas. Learning curve and rate adjustment models: Comparative prediction accuracy under varying conditions. Naval Postgraduate School, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

G, Sigari, Costi T, Michigan State University. Division of Engineering Research., and United States. National Aeronautics and Space Administration., eds. Effect of accuracy of wind power prediction on power system operator: Final report. College of Engineering, Michigan State University, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Hanson, R. Karl. The accuracy of recidivism risk assessments for sexual offenders: A meta-analysis. Public Safety and Emergency Preparedness Canada, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Alfred, Buch. Improvement of fatigue life prediction accuracy for various realistic loading spectra by use of correction factors. Technion-Israel Institute of Technology, Dept. of Aeronautical Engineering, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Charuk, Kerry A. Accuracy in prediction of personality as a function of sex length of description, task order, and actual score. Laurentian University, Department of Psychology, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Terlecki-Zaniewicz, Georg. Community evaluation of crowd-sourced ideas: An explorative study on how to improve the prediction accuracy of crowdsourcing communities. AV Akademikerverlag, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

A, Lipa John, and United States. National Aeronautics and Space Administration., eds. High accuracy thermal conductivity measurements near the lambda transition of helium with very high temperature resolution: Final report for NASA-FIR grant #NAG 2-276. National Aeronautics and Space Administration, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Prediction of Accuracy result"

1

Cheng, Qian, Xinyu Jiao, Mengmeng Yang, Mingliang Yang, Kun Jiang, and Diange Yang. "Advancing Autonomous Driving Safety Through LLM Enhanced Trajectory Prediction." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_71.

Full text
Abstract:
AbstractIn recent years, there has been remarkable progress in autonomous driving technology. To improve the safety of autonomous driving comprehensively, accurate predictions for all traffic agents are crucial. Typically, the graph neural network is widely employed for the trajectory prediction. To enhance the prediction accuracy rate, this paper utilizes a finetuned vision-to-language large model to extract driving intentions. With the well-designed prompt and the supervision of the specific dataset, the LLM (large language model) can analyze the current traffic condition and give the corres
APA, Harvard, Vancouver, ISO, and other styles
2

Kjeldsberg, Fabian, Ziaul Haque Munim, Morten Bustgaard, Sahil Bhagat, Emilia Lindroos, and Per Haavardtun. "Sensitivity of Predictive Performance Assessment Accuracy in Varying k-fold Cross Validation." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-84170-5_7.

Full text
Abstract:
Abstract In machine learning (ML) applications, cross-validation (CV) allows greater generalizability of a trained algorithm over out-of-sample or new data. This study explores the accuracy of trained ML algorithms in predicting student performance in a maritime simulator exercise scenario in four different k-fold CVs. Three, five, eight, and ten-fold CVs were trained using a cloud-ML platform. Three top-performing ML algorithms were evaluated considering log loss, accuracy, and area under the curve (AUC). The results indicate higher predictive accuracy with increasing k in CV folds. Consideri
APA, Harvard, Vancouver, ISO, and other styles
3

Mostofi, Fatemeh, Onur Behzat Tokdemir, and Vedat Toğan. "Leveraging Variational Autoencoder for Improved Construction Progress Prediction Performance." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4355-1_51.

Full text
Abstract:
AbstractThe imbalanced construction dataset reduces the accuracy of the machine learning model. This issue that addressed by recent construction management research through different sampling approaches. Despite their advantages, the utilized sampling approaches are reducing the reliability of the prediction model, while posing the risk of artificial bias. The objective of this study is to address the challenge of imbalanced datasets in construction progress prediction models using a novel variational autoencoder (VAE) that generates synthetic data for underrepresented classes. The VAE's encod
APA, Harvard, Vancouver, ISO, and other styles
4

Qian, Shenghua. "Vehicle Collision Prediction Model on the Internet of Vehicles." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_53.

Full text
Abstract:
AbstractAn active collision prediction model on the Internet of Vehicles is proposed. Through big data calculation on the cloud computing platform, the model predicts whether the vehicles may collide and the time of the collision, so the server actively sends warning signals to the vehicles that may collide. Firstly, the vehicle collision prediction model preprocesses the data set, and then constructs a new feature set through feature engineering. For the imbalance of the data set, which affects predictive results, SMOTE algorithm is proposed to generate new samples. Then, the LightGBM algorit
APA, Harvard, Vancouver, ISO, and other styles
5

Rio, Simon, Alain Charcosset, Tristan Mary-Huard, Laurence Moreau, and Renaud Rincent. "Building a Calibration Set for Genomic Prediction, Characteristics to Be Considered, and Optimization Approaches." In Methods in Molecular Biology. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2205-6_3.

Full text
Abstract:
AbstractThe efficiency of genomic selection strongly depends on the prediction accuracy of the genetic merit of candidates. Numerous papers have shown that the composition of the calibration set is a key contributor to prediction accuracy. A poorly defined calibration set can result in low accuracies, whereas an optimized one can considerably increase accuracy compared to random sampling, for a same size. Alternatively, optimizing the calibration set can be a way of decreasing the costs of phenotyping by enabling similar levels of accuracy compared to random sampling but with fewer phenotypic
APA, Harvard, Vancouver, ISO, and other styles
6

Hiraga, Tojuro, and Taichi Shiiba. "Surrogate Modeling of Suspensions with High Stiffness Element for Real-Time Analysis Using Machine Learning." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_57.

Full text
Abstract:
AbstractThe aim of this study is to generate a surrogate model of a suspension system with high stiffness elements for real-time analysis using machine learning. A Long Short-Term Memory networks was used as a machine learning method to generate surrogate models for three-degree-of-freedom quarter car model with a bush element. To evaluate the performance of the machine learning models, the simulation results and computation time were compared with the 3DOF model. As a result, it was confirmed that the response of the body acceleration was predicted with good accuracy by predicting the bush de
APA, Harvard, Vancouver, ISO, and other styles
7

Warmuth, Christian, and Henrik Leopold. "On the Potential of Textual Data for Explainable Predictive Process Monitoring." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27815-0_14.

Full text
Abstract:
AbstractPredictive process monitoring techniques leverage machine learning (ML) to predict future characteristics of a case, such as the process outcome or the remaining run time. Available techniques employ various models and different types of input data to produce accurate predictions. However, from a practical perspective, explainability is another important requirement besides accuracy since predictive process monitoring techniques frequently support decision-making in critical domains. Techniques from the area of explainable artificial intelligence (XAI) aim to provide this capability an
APA, Harvard, Vancouver, ISO, and other styles
8

Rüttgers, Mario, Seong-Ryong Koh, Jenia Jitsev, Wolfgang Schröder, and Andreas Lintermann. "Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59851-8_6.

Full text
Abstract:
Abstract Using traditional computational fluid dynamics and aeroacoustics methods, the accurate simulation of aeroacoustic sources requires high compute resources to resolve all necessary physical phenomena. In contrast, once trained, artificial neural networks such as deep encoder-decoder convolutional networks allow to predict aeroacoustics at lower cost and, depending on the quality of the employed network, also at high accuracy. The architecture for such a neural network is developed to predict the sound pressure level in a 2D square domain. It is trained by numerical results from up to 20
APA, Harvard, Vancouver, ISO, and other styles
9

Shang, Zhiqiang, Yerong Hu, Xiangyin Chen, Shiyu Liu, and Zejun Zhang. "Technical Degradation Prediction of Bridge Components Based on Semi-Markov Degradation Model." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4355-1_2.

Full text
Abstract:
AbstractTo overcome the limitations of traditional Markov bridge degradation prediction models, which fail to consider the interactions between different component degradation mechanisms and struggle to accurately capture the true degradation conditions of bridge components, introducing an improved version of the traditional Markov model by incorporating the Weibull distribution. This enhancement results in a semi-Markov model that offers a probability distribution for predicting the technical condition of bridge components. Taking advantage of periodic inspection data from a highway section i
APA, Harvard, Vancouver, ISO, and other styles
10

Chen, Yanbo, Huilong Yu, and Junqiang Xi. "STS-GAN: Spatial-Temporal Attention Guided Social GAN for Vehicle Trajectory Prediction." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_24.

Full text
Abstract:
AbstractAccurately predicting the trajectories of other vehicles is crucial for autonomous driving to ensure driving safety and efficiency. Recently, deep learning techniques have been extensively employed for trajectory prediction, resulting in significant advancements in predictive accuracy. However, existing studies often fail to explicitly distinguish the impact of historical inputs at different time steps and the influence of surrounding vehicles at distinct locations. Moreover, deep learning-based approaches generally lack model interpretation. To overcome the issues, we propose the Spat
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Prediction of Accuracy result"

1

Venkatesh, B., and G. Ramkumar. "Enhanced Accuracy and Prediction of Novel Convolutional Neural Networks Compared over ResNet Algorithm in Predicting Student Career Classification." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725959.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Kolts, Juri, Michael W. Joosten, and Probjot Singh. "An Engineering Approach to Corrosion/Erosion Prediction." In CORROSION 2006. NACE International, 2006. https://doi.org/10.5006/c2006-06560.

Full text
Abstract:
Abstract The corrosion and erosion predictions involve verification or derivation from the parameters in the Basis of Design for new oil and gas developments. The field design and operating data are partly developed from reservoir analyses, flow simulations, and thermodynamic models. These models provide necessary data to obtain the parameters controlling corrosion and erosion. One responsibility of a materials or corrosion engineer is to assure that engineers in the other disciplines develop the field specific information that is required for materials selection and corrosion control. With th
APA, Harvard, Vancouver, ISO, and other styles
3

Yang, Tianxiao, Kenneth Brentner, Greg Walsh, and Yaowei Li. "A Dual Compact Model for Rotor Noise Prediction." In Vertical Flight Society 71st Annual Forum & Technology Display. The Vertical Flight Society, 2015. http://dx.doi.org/10.4050/f-0071-2015-10068.

Full text
Abstract:
This paper examines the applicability and robustness of the dual compact thickness noise model for a wide variety of cases. Three major parameters are considered: airfoil, blade planform, and advancing-tip Mach number. The computation results (acoustic pressure time history and spectrum) indicate that generally, dual compact thickness noise is in good agreement with normal thickness noise for all the cases examined in this paper, but the approximation is approximately 24 times faster. The chord length and advancing-tip Mach number have the most impact on the accuracy of the dual compact thickn
APA, Harvard, Vancouver, ISO, and other styles
4

Herrera-Ruiz, Juan Federico, Javier Fontalvo, and Oscar Andr�s Prado-Rubio. "Hybrid model development for Succinic Acid fermentation: relevance of ensemble learning for enhancing model prediction." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.153338.

Full text
Abstract:
Sustainable development goals have spurred advancements in bioprocess design, driven by improved process monitoring, data storage, and computational power. High-fidelity models are essential for advanced process system engineering, yet accurate parametric models for bioprocessing remain challenging due to overparameterization, often resulting in poor predictive accuracy. Hybrid modeling, combining parametric and non-parametric methods, offers a promising solution by enhancing accuracy while maintaining interpretability. This study explores hybrid models for succinic acid fermentation by Escher
APA, Harvard, Vancouver, ISO, and other styles
5

Junior, Jailson, and Cláudio Campelo. "League of Legends: Real-Time Result Prediction." In Congresso Brasileiro de Inteligência Computacional. SBIC, 2023. http://dx.doi.org/10.21528/cbic2023-161.

Full text
Abstract:
This paper presents a study on the prediction of outcomes in matches of the electronic game League of Legends (LoL) using machine learning techniques. With the aim of exploring the ability to predict real-time results, considering different variables and stages of the match, we highlight the use of unpublished data as a fundamental part of this process. With the increasing popularity of LoL and the emergence of tournaments, betting related to the game has also emerged, making the investigation in this area even more relevant. A variety of models were evaluated and the results were encouraging.
APA, Harvard, Vancouver, ISO, and other styles
6

Vikram, Yaragala, and P. Gururama Senthilvel. "Efficient framework for sports result prediction using random forest and compare the accuracy with XGBoost." In INTERNATIONAL CONFERENCE ON APPLICATION OF ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SOURCES AND ENVIRONMENTAL SUSTAINABILITY. AIP Publishing, 2025. https://doi.org/10.1063/5.0259242.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Gupta, Yashodhan, Onkar Awate, Sejal Pawar, Chetan N. Aher, and Sanika Bhalerao. "Integrated Analytics and Prediction of Heart Disease, Diabetes, and Parkinson’s Using Logistic Regression and SVM Models." In The Second International Conference of AI new Technology and open Discussion. Algorithm Lab, 2025. https://doi.org/10.63211/j.p.25.645331.

Full text
Abstract:
Chronic illnesses like diabetes, heart disease, and Parkinson's require early diagnosis for proper management and better health outcomes. This paper introduces an AI-based platform that forecasts the risk of these diseases based on machine learning models. Support Vector Machines (SVM) are used for precise detection of Parkinson's and diabetes, whereas Logistic Regression is used for effective heart disease prediction. SVM model resulted in 78% accuracy in predicting diabetes, and Logistic Regression provided 85% accuracy for heart disease prediction. SVM attained an accuracy of 87% in predict
APA, Harvard, Vancouver, ISO, and other styles
8

Omer, Pareekhan. "Improving Prediction Accuracy of Lasso and Ridge Regression as an Alternative to LS Regression to Identify Variable Selection Problems." In 3rd International Conference of Mathematics and its Applications. Salahaddin University-Erbil, 2020. http://dx.doi.org/10.31972/ticma22.05.

Full text
Abstract:
This paper introduces the Lasso and Ridge Regression methods, which are two popular regularization approaches. The method they give a penalty to the coefficients differs in both of them. L1 Regularization refers to Lasso linear regression, while L2 Regularization refers to Ridge regression. As we all know, regression models serve two main purposes: explanation and prediction of scientific phenomena. Where prediction accuracy will be optimized by balancing each of the bias and variance of predictions, while explanation will be gained by constructing interpretable regression models by variable s
APA, Harvard, Vancouver, ISO, and other styles
9

Adeeyo, Yisa. "Random Forest Ensemble Model for Reservoir Fluid Property Prediction." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/212044-ms.

Full text
Abstract:
Abstract Reservoir fluid PVT properties are measured in the laboratory for various use in reservoir engineering evaluation and estimation. Despite the indispensability of these PVT parameters, PVT lab data are seldomly available and if available may be unreliable. Instead, various empirical models have been developed and used in the industry. These empirical models are inherently inaccurate when used to predict PVT properties of fluid from different geological region with different depositional environment and fingerprint. Artificial Intelligence (AI) has evolved over the years and provided so
APA, Harvard, Vancouver, ISO, and other styles
10

Qian, Shaoxiang, and Shinichiro Kanamaru. "Benchmark Study of CFD-Based Prediction Accuracy of the Models Evaluating Particle and Droplet Induced Erosion for Engineering Applications." In ASME 2020 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/pvp2020-21685.

Full text
Abstract:
Abstract The particles (including solid particles and liquid droplets) existing in multi-phase flow in process plants can cause erosion due to flow turbulence, and thus, result in pipe wall thinning. Hence, it is important to evaluate erosion rate for determining design margin and finding counter-measures. Many models have been proposed for predicting particles induced erosion rate, but there is significant disparity in their prediction accuracy. The present study aims to verify prediction accuracy of some major erosion models utilizing the published experimental data, for applications to engi
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Prediction of Accuracy result"

1

Holzenthal, Elizabeth, and Bradley Johnson. Comparison of run-up models with field data. Engineer Research and Development Center (U.S.), 2024. https://doi.org/10.21079/11681/49470.

Full text
Abstract:
Run-up predictions are inherently uncertain, owing to ambiguities in phase-averaged models and inherent complexities of surf and swash-zone hydrodynamics. As a result, different approaches, ranging from simple algebraic expressions to computationally intensive phase-resolving models, have been used in attempt to capture the most relevant run-up processes. Studies quantifiably comparing these methods in terms of physical accuracy and computational speed are needed as new observation technologies and models become available. The current study tests the capability of the new swash formulation of
APA, Harvard, Vancouver, ISO, and other styles
2

Mosalam, Khalid, Issac Pang, and Selim Gunay. Towards Deep Learning-Based Structural Response Prediction and Ground Motion Reconstruction. Pacific Earthquake Engineering Research Center, 2025. https://doi.org/10.55461/ipos1888.

Full text
Abstract:
This research presents a novel methodology that uses Temporal Convolutional Networks (TCNs), a state-of-the-art deep learning architecture, for predicting the time history of structural responses to seismic events. By leveraging accelerometer data from instrumented buildings, the proposed approach complements traditional structural analysis models, offering a computationally efficient alternative to nonlinear time history analysis. The methodology is validated across a broad spectrum of structural scenarios, including buildings with pronounced higher-mode effects and those exhibiting both line
APA, Harvard, Vancouver, ISO, and other styles
3

Tuniki, Himanshu Patel, Gabriel Bekö, and Andrius Jurelionis. Using Adaptive Behaviour Patterns of Open Plan Office Occupants in Energy Consumption Predictions. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541563857.

Full text
Abstract:
One of the factors that affects energy consumption in buildings is the level of control that occupants have over their environment, as well as their adaptive behaviour. The aim of this study was to focus on the adaptive clothing behaviour pattern, and to analyse its impact on energy consumption when integrated into a dynamic energy prediction tool. A questionnaire survey was conducted in an office building to collect the occupant behaviour data. The occupant clothing levels and the window opening behaviour were integrated into the dynamic energy performance prediction software, IDA ICE. The re
APA, Harvard, Vancouver, ISO, and other styles
4

Bhurtyal, Sanjeev, Hieu Bui, Sarah Hernandez, et al. Prediction of waterborne freight activity with Automatic Identification System using machine learning. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49794.

Full text
Abstract:
This paper addresses latency issues related to publicly available port-level commodity tonnage reports. Predicting commodity tonnage at the port-level, near real time vessel tracking data is used with historical WCS with a machine learning model. Commodity throughput is derived from WCS data which is released publicly approximately two years after collection. This latency presents a challenge for short-term planning and other operational uses. This study leverages near real time vessel tracking data from the AIS data set. LSTM, TCN, and TFT machine learning models are developed using the featu
APA, Harvard, Vancouver, ISO, and other styles
5

Gungor, Osman, Imad Al-Qadi, and Navneet Garg. Pavement Data Analytics for Collected Sensor Data. Illinois Center for Transportation, 2021. http://dx.doi.org/10.36501/0197-9191/21-034.

Full text
Abstract:
The Federal Aviation Administration instrumented four concrete slabs of a taxiway at the John F. Kennedy International Airport to collect pavement responses under aircraft and environmental loading. The study started with developing preprocessing scripts to organize, structure, and clean the collected data. As a result of the preprocessing step, the data became easier and more intuitive for pavement engineers and researchers to transform and process. After the data were cleaned and organized, they were used to develop two prediction models. The first prediction model employs a Bayesian calibra
APA, Harvard, Vancouver, ISO, and other styles
6

Puttanapong, Nattapong, Arturo M. Martinez Jr, Mildred Addawe, Joseph Bulan, Ron Lester Durante, and Marymell Martillan. Predicting Poverty Using Geospatial Data in Thailand. Asian Development Bank, 2020. http://dx.doi.org/10.22617/wps200434-2.

Full text
Abstract:
This study examines an alternative approach in estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial distribution of poverty in Thailand. It also compares the predictive performance of various econometric and machine learning methods such as generalized least squares, neural network, random forest, and support vector regression. Results suggest that intensity of night lights and other variables that approximate population density are highly associated with the proportion of population living in poverty. The random forest technique yiel
APA, Harvard, Vancouver, ISO, and other styles
7

Cho, Seonghwan, Tandra Bagchi, Jongmyung Jeon, and John E. Haddock. Material Characterization and Determination of MEPDG Input Parameters for Indiana Superpave 5 Asphalt Mixtures. Purdue University, 2024. http://dx.doi.org/10.5703/1288284317725.

Full text
Abstract:
Superpave 5 (SP 5) has the ability to slow asphalt binder aging in asphalt pavements, which is why the SP 5 mix with optimum asphalt binder content to yield 5% air voids has recently been used in Indiana roads. INDOT also uses the AASHTOWare Pavement ME design software in pavement design, and the current asphalt aging prediction model in Pavement ME was developed based on the conventional Superpave asphalt mixture (design air voids 4%) design method. For the successful use of the SP 5 mixture design method with Pavement ME, the input level and input parameters play a significant role. The obje
APA, Harvard, Vancouver, ISO, and other styles
8

Slone, Scott Michael, Marissa Torres, Nathan Lamie, Samantha Cook, and Lee Perren. Automated change detection in ground-penetrating radar using machine learning in R. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49442.

Full text
Abstract:
Ground-penetrating radar (GPR) is a useful technique for subsurface change detection but is limited by the need for a subject matter expert to process and interpret coincident profiles. Use of a machine learning model can automate this process to reduce the need for subject matter expert processing and interpretation. Several machine learning models were investigated for the purpose of comparing coincident GPR profiles. Based on our literature review, a Siamese Twin model using a twinned convolutional network was identified as the optimum choice. Two neural networks were tested for the interna
APA, Harvard, Vancouver, ISO, and other styles
9

Gunay, Selim, Fan Hu, Khalid Mosalam, et al. Blind Prediction of Shaking Table Tests of a New Bridge Bent Design. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, 2020. http://dx.doi.org/10.55461/svks9397.

Full text
Abstract:
Considering the importance of the transportation network and bridge structures, the associated seismic design philosophy is shifting from the basic collapse prevention objective to maintaining functionality on the community scale in the aftermath of moderate to strong earthquakes (i.e., resiliency). In addition to performance, the associated construction philosophy is also being modernized, with the utilization of accelerated bridge construction (ABC) techniques to reduce impacts of construction work on traffic, society, economy, and on-site safety during construction. Recent years have seen s
APA, Harvard, Vancouver, ISO, and other styles
10

Ramakrishnan, Aravind, Fangyu Liu, Angeli Jayme, and Imad Al-Qadi. Prediction of Pavement Damage under Truck Platoons Utilizing a Combined Finite Element and Artificial Intelligence Model. Illinois Center for Transportation, 2024. https://doi.org/10.36501/0197-9191/24-030.

Full text
Abstract:
For robust pavement design, accurate damage computation is essential, especially for loading scenarios such as truck platoons. Studies have developed a framework to compute pavement distresses as function of lateral position, spacing, and market-penetration level of truck platoons. The established framework uses a robust 3D pavement model, along with the AASHTOWare Mechanistic–Empirical Pavement Design Guidelines (MEPDG) transfer functions to compute pavement distresses. However, transfer functions include high variability and lack physical significance. Therefore, as an improvement to effecti
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Prediction of Accuracy result' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography