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Relevant bibliographies by topics / Neural calendar

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Academic literature on the topic 'Neural calendar'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Neural calendar"

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Allawi, Ziyad T. "A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq." Computation 10, no. 10 (2022): 186. http://dx.doi.org/10.3390/computation10100186.

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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of

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Meng, Ming, Dong Xiao Niu, Wei Sun, and Wei Shang. "Research on Monthly Electric Energy Demand Forecasting under the Influence of Two Calendars." Applied Mechanics and Materials 20-23 (January 2010): 963–68. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.963.

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Monthly electric energy demand forecasting plays an important role for the running of power system. China has two tow calendars and they works at the same time. Holidays designed by the lunar calendar affect the regularity of monthly electric load recorded only by the Gregorian one. The normal fuzzy transform is advanced here to quantitatively describe the impact of the Spring Festival and further divided the influence into Jan. and Feb. After excluding the influence, the amended historical data are adopted to training RBF neural network. Experiment results show that because the regularity of

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Vasu, Sharma, and Satish Saini Dr. "Prediction of Power Loss in Grid Using Neural Network." International Journal of Innovative Research in Engineering and Management (IJIREM) 10, no. 04 (2023): 77–85. https://doi.org/10.55524/ijirem.2023.10.4.9.

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This Paper proposes a data-driven approach for grid loss prediction in power systems. It utilizes a comprehensive dataset with relevant features such as grid load, temperature forecasts, and calendar data. The dataset is pre-processed by handling missing values, normalizing features, and encoding cyclic calendar features. A Long Short-Term Memory (LSTM) recurrent neural network is employed for the prediction model, capturing temporal dependencies and generating forecasts of grid loss two hours ahead. The model is trained using mean absolute error (MAE) as the loss function and optimized throug

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Hofman, Michel A. "The brains calendar: neural mechanisms of seasonal timing." Biological Reviews 79, no. 1 (2004): 61–77. http://dx.doi.org/10.1017/s1464793103006250.

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Nhita, Fhira, Adiwijaya, U. N. Wisesty, and Izzatul Ummah. "PLANTING CALENDAR FORECASTING SYSTEM USING EVOLVING NEURAL NETWORK." Far East Journal of Electronics and Communications 14, no. 2 (2015): 81–92. http://dx.doi.org/10.17654/fjecjun2015_081_092.

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Chenchen, Li, Fu Yuan, Wang Xiaolin, Dong Shulong, and Song Ziwen. "MATLAB network model simulation based on BP neural network." Journal of Scientific and Engineering Research 8, no. 7 (2021): 96–104. https://doi.org/10.5281/zenodo.10608864.

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<strong>Abstract</strong> With the development of china's economy this year, the demand for automobiles is increasing, so the number of car accidents in the country each year is also more and more concerned, this paper first collects the number of car accidents in the national calendar year, and then uses these data to make predictions with MATLAB using BP neural network model and improved radial base function network, and finally analyzes the advantages and disadvantages of the model according to the prediction results, so as to achieve a deep understanding of the principle and application of

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Fitriana, Gita Fadila, and Novian Adi Prasetyo. "Rice Planting Calendar Application Development using Scrum." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 16, no. 2 (2022): 169. http://dx.doi.org/10.22146/ijccs.70155.

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Indonesia is an agricultural country that produces more rice commodities than secondary crops. Many people who work as farmers choose the land to plant rice. Farmers experience several obstacles in determining the correct planting time to improve the rice harvest quality. A planting calendar is a method used by farmers to determine the scheduling of planting for one year. The rice planting calendar works based on rainfall and climate patterns. With the help of the latest technology, determining the rice planting calendar can be done quickly. The utilization of computer technology and algorithm

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Jiang, Hui, Mingzhe Zhu, Jun Li, et al. "Data Mining Based on Chinese Traditional Calendar in the Han Dynasty Yang Mausoleum Museum." Applied Sciences 9, no. 24 (2019): 5442. http://dx.doi.org/10.3390/app9245442.

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The Outer Burial Pits of the Han Dynasty Yang Mausoleum is the first fully enclosed site museum in China. The Internet of things sensor installed in the pavilion has accumulated more than 7,000,000 heterogeneous data. Traditional algorithms, such as temperature prediction model, only use statistical value to predict the trend of temperature change, so the data utilization rate is insufficient. In addition, the accuracy of prediction model is also relatively low. The extreme learning machine is a single layer feedback neural network learning method. Using extreme learning machine to analyze and

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Nguyen, Tuan-Dung, and Thanh-Phuong Nguyen. "LOAD FORECASTING FOR MONTHS OF THE LUNAR NEW YEAR HOLIDAY USING STANDARDIZED LOAD PROFILE AND SUPPORT REGRESSION VECTOR: CASE STUDY HO CHI MINH CITY." JOURNAL OF TECHNOLOGY & INNOVATION 1, no. 1 (2020): 01–05. http://dx.doi.org/10.26480/jtin.01.2021.01.05.

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Load forecasting plays an important role in building business strategies, ensuring reliability and safe operation for any electrical system. There are many different methods, including: regression models, time series, neural networks, expert systems, fuzzy logic, machine learning and statistical algorithms used for short-term forecasts. However, the practical requirement is how to minimize the forecast errors to prevent power shortages or wastage in the electricity market and limit risks. For Asian countries (such as Vietnam) that use lunar calendar, one of the most difficult and unpredictable

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Dung Nguyen, Tuan, and Thanh Phuong Nguyen. "LOAD FORECASTING FOR MONTHS OF THE LUNAR NEW YEAR HOLIDAY USING STANDARDIZED LOAD PROFILE AND SUPPORT REGRESSION VECTOR: CASE STUDY HO CHI MINH CITY." JOURNAL OF TECHNOLOGY & INNOVATION 1, no. 1 (2020): 01–06. http://dx.doi.org/10.26480/jtin.01.2021.01.06.

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Load forecasting plays an important role in building business strategies, ensuring reliability and safe operation for any electrical system. There are many different methods, including: regression models, time series, neural networks, expert systems, fuzzy logic, machine learning and statistical algorithms used for short-term forecasts. However, the practical requirement is how to minimize the forecast errors to prevent power shortages or wastage in the electricity market and limit risks. For Asian countries (such as Vietnam) that use lunar calendar, one of the most difficult and unpredictable

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Books on the topic "Neural calendar"

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Books, D. M. S. 2028: Neutral Alpine Fern Pattern Weekly Calendar Planner Organizer. Independently Published, 2019.

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Books, D. M. S. 2020: Neutral Alpine Fern Pattern Weekly Calendar Planner Organizer. Independently Published, 2019.

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Scott, Evin, and Andrea Scott. Mom's Calendar Journal : Organizing Yourself & Recording Baby's First Year: Gender Neutral/Green. Lulu Press, Inc., 2021.

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Pages, Peechy. January - December - 2020 Weekly + Monthly Planner: Hand Painted Neutral Stripes - Weekly Calendar with Quotes + Agenda Organizer. Independently Published, 2019.

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McClure, Zoe Zoe. Neutral Boho Yoga Ornate Mandala Peace Sign Hippie: Best Yoga Day Gift 2021, Yoga Teaching Journal Calendar, Yogi Gifts for Women. Independently Published, 2021.

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Davis, Jenny B. Style Wise. 3rd ed. Bloomsbury Publishing Inc, 2024. http://dx.doi.org/10.5040/9781501392405.

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Style Wise: A Practical Guide to Becoming a Fashion Stylist, Third Edition is an essential text for turning aspiring stylists into professional stylists. The text presents fashion styling as a form of communication that can both support and challenge social norms such as beauty standards and gender roles. Full-color photos and examples from the runway reflect the fast-paced, vibrant fashion industry and cover topics including photo shoots, fashion shows, and special events. Step-by-step instructions guide readers through crucial areas like business basics, establishing a social media presence,

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Book chapters on the topic "Neural calendar"

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Xiao, Chunjing, Zexuan Yu, Wei Fan, Honghai Zhang, and Xuecheng Wu. "Session-Based Sequence Recommendation with Calendar Airport Graph Neural Networks for Dynamic Pricing." In Communications in Computer and Information Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-6957-8_7.

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Prentza Andriana, Imholz Ben PM, Gizdulich Paolo, Parati Gianfranco, and Wesseling Karel H. "Is the estimation of human age derived from ambulatory blood pressure waveform analysis stable over the 24 hours?" In Studies in Health Technology and Informatics. IOS Press, 1999. https://doi.org/10.3233/978-1-60750-904-2-153.

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In a previous study we developed a method to estimate a person&apos;s age based on 10 s episodes of arterial pressure pulsations using a neural net technique. The pulsations were recorded in the morning in supine or semi-reclining position in rest. We wondered if the age estimation techniques would produce systematically different values under ambulatory conditions, during night or day, in other postures, over the 24 hours. We, therefore, analyzed 10 s episodes each half hour over the 24 hours in 12 previously recorded persons aged 19 to 58 years, applying the waveforms to the same neural

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Yucesan, Melih, Suleyman Mete, Faruk Serin, Erkan Celik, and Muhammet Gul. "NARX Neural Networks Model for Forecasting Daily Patient Arrivals in the Emergency Department." In Advances in Healthcare Information Systems and Administration. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2581-4.ch001.

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Regarding measuring of service quality at the emergency departments (ED), essential parameters are length of stay (LOS) and waiting times. Patient arrivals, which is related to LOS and waiting times, is hard to forecast and is affected by many parameters. Therefore, authors employed a Nonlinear Autoregressive Exogenous (NARX) model for forecasting of ED arrivals. NARX models are used extensively in many applications that show non-linear and dynamic behavior, but as far as authors know, the NARX method has not yet been used in the forecast of ED arrivals before. In this study, calendar and clim

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Yucesan, Melih, Muhammet Gul, Suleyman Mete, and Erkan Celik. "A Forecasting Model for Patient Arrivals of an Emergency Department in Healthcare Management Systems." In Advances in Healthcare Information Systems and Administration. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7071-4.ch012.

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Emergency departments (EDs) are one of the most valuable departments of healthcare management systems. Patient arrivals at the EDs are crucial for planning of the future. Accurate forecasting of patient arrivals contributes to better organized human resources and medical devices in the EDs. Therefore, in this chapter, the authors aim to develop a hybrid model including the methods of autoregressive integrated moving average with external variables (ARIMAX) and artificial neural network (ANN) in a hospital ED. The arrival data was collected from the hospital information system of a public hospi

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Panksepp, Jaak. "Sleep, Arousal, and Mythmaking in the Brain." In Affective Neuroscience. Oxford University PressNew York, NY, 1998. http://dx.doi.org/10.1093/oso/9780195096736.003.0007.

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Abstract Shakespeare proposed one possible function of sleep when he suggested that it “knits up the raveled sleeve of care.” A great number of functions have now been attributed to sleep and dreaming, but few have been definitively demonstrated with the tools of science. One thing is certain, though. Each day our lives cycle through the master routines of sleeping, dreaming, and waking. All our activities are guided by the age-old rhythms of nature, and many neural mechanisms assure that we remain in tune with the cycling of days and nights across the seasons. Our brains contain endogenous da

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Grafton, Anthony. "Humanist Chronology (III): The Romance of Ritual." In Joseph Scaliger. Oxford University PressOxford, 1993. http://dx.doi.org/10.1093/oso/9780199206018.003.0005.

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Abstract Calendars are far more than neutral devices for the measurement of time. Ancient calendars, in particular, played several—different but equally vital—roles in Greek and Roman society and culture. They determined the round of propitiatory and commemorative rituals by which an ancient people or city remained in touch with the shaping events of its past, asked its gods for protection in the future—and, as the enemies of Athenian democracy complained, delayed business in the present by closing down the courtroom and the assembly. They contained days both propitious and impropitious for an

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Dodda, Abhishek. "Understanding agentic artificial intelligence: Autonomous digital agents and their impact on workflows and decisions." In Artificial Intelligence and Financial Transformation: Unlocking the Power of Fintech, Predictive Analytics, and Public Governance in the Next Era of Economic Intelligence. Deep Science Publishing, 2025. https://doi.org/10.70593/978-81-988918-1-5_3.

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What if an AI chatbot could operate a task entirely on its own in software and/or hardware? What if, when you asked your favorite AI chatbot to schedule a meeting with someone, it created your calendar appointment, contacted the person, negotiated the time slot, and sent reminders, handling any situation that arose, entirely without your further input? These so-called "autonomous" or "agentic" AI models are rapidly emerging. In this chapter, we explain how autonomous AI systems already exist now and provide an overview of what they can do. We also discuss the implications this new AI paradigm

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Conference papers on the topic "Neural calendar"

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Zhang, Yong, Hao Zhang, Huixuan Wang, Rentao Gu, Lianlian Yang, and Jiansong Miao. "FlexE Calendar Slot Allocation Algorithm Based on Recurrent Neural Network Prediction." In 2022 20th International Conference on Optical Communications and Networks (ICOCN). IEEE, 2022. http://dx.doi.org/10.1109/icocn55511.2022.9901275.

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Wang, Daheng, Meng Jiang, Munira Syed, et al. "Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors." In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2020. http://dx.doi.org/10.1145/3394486.3403308.

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Feng, Cong, and Jie Zhang. "Short-Term Load Forecasting With Different Aggregation Strategies." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-86084.

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Effective short-term load forecasting (STLF) plays an important role in demand-side management and power system operations. In this paper, STLF with three aggregation strategies are developed, which are information aggregation (IA), model aggregation (MA), and hierarchy aggregation (HA). The IA, MA, and HA strategies aggregate inputs, models, and forecasts, respectively, at different stages in the forecasting process. To verify the effectiveness of the three aggregation STLF, a set of 10 models based on 4 machine learning algorithms, i.e., artificial neural network, support vector machine, gra

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Gunawansyah, Thee Houw Liong, and Adiwijaya. "Prediction and anomaly detection of rainfall using evolving neural network to support planting calender in soreang (Bandung)." In 2017 5th International Conference on Information and Communication Technology (ICoIC7). IEEE, 2017. http://dx.doi.org/10.1109/icoict.2017.8074671.

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Selvi, M. Vetri, and Sukumar Mishra. "Impact of Presence of Calender Feature in the Performance of Day-Ahead Electric Load Power Forecasting with New Framework Realized in Artificial Neural Network Tehinique using Matlab Programming." In 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES). IEEE, 2018. http://dx.doi.org/10.1109/icpeices.2018.8897343.

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Berry, Irene, Glen Merfeld, and Patrick Riley. "Mapping Energy Storage Physics to Application Economics." In ASME 2016 10th International Conference on Energy Sustainability collocated with the ASME 2016 Power Conference and the ASME 2016 14th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/es2016-59597.

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The success of grid scale energy storage hinges on our ability to solve real problems economically. By mapping energy storage physics to application economics, this paper offers a technology neutral look at how energy storage can solve real problems. A value analytics methodology was developed that combines the physics of energy storage, application power commands, and market-specific economic constructs. This approach evaluates and optimizes the value of energy storage for specific projects by providing insight into the tradeoffs between the lifecycle costs and revenues. These analytics calcu

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