Academic literature on the topic 'Kepler's Algorithm'

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Journal articles on the topic "Kepler's Algorithm"

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Mahmoud, Shakir Wahab. "Wireless Sensor Network (WSN) Energy-Efficient Clustering and Routing: Evaluating Kepler's Algorithm Alongside K-Means." Engineering and Technology Journal 10, no. 05 (2025): 4855–64. https://doi.org/10.5281/zenodo.15349846.

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Wireless Sensor Networks (WSNs) find applications in a broad spectrum of fields, including but not limited to military surveillance and environmental monitoring, where energy efficiency is a key performance indicator because of sensor node power constraint. Implementation of low energy-consumption clustering and routing protocols is pivotal in optimizing network life by minimizing energy consumption. This paper discusses the collaboration of Kepler's Algorithm with the K-means clustering algorithm for improving energy efficiency in WSNs. Kepler's Algorithm, which is planetary motion dynamics-b
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Conway, Bruce A. "An improved algorithm due to laguerre for the solution of Kepler's equation." Celestial Mechanics 39, no. 2 (1986): 199–211. http://dx.doi.org/10.1007/bf01230852.

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CHIPADE, Radhika A., and Thekke Variyam RAMANATHAN. "Extended Kalman filter based statistical orbit determination for geostationary and geosynchronous satellite orbits in BeiDou constellation." Contributions to Geophysics and Geodesy 51, no. 1 (2021): 25–46. http://dx.doi.org/10.31577/congeo.2021.51.1.2.

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BeiDou Navigation Satellite System (BDS) is composed of satellites in geostationary Earth orbit (GEO), medium Earth orbit (MEO) and inclined geosynchronous orbit (IGSO). However, the orbit determination of geostationary Earth orbits and of geosynchronous orbits (GSO) with small inclination angle and small eccentricity is a challenging task that is addressed in this paper using Extended Kalman Filter (EKF). The satellite positions were predicted in Earth-centred inertial (ECI) reference frame when propagated through Keplerian model and perturbation force model for different values of right asce
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Chen, Xiao Liang, Jian Xun Chen, and Hao Liu. "Large-Scale Virtual Simulation of the Solar System Based on Java3D." Applied Mechanics and Materials 721 (December 2014): 459–63. http://dx.doi.org/10.4028/www.scientific.net/amm.721.459.

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As the modeling of the solar system is difficult and inaccurate, the 3D modeling of the planets in the solar system is studied by using Java3D technology. To make the revolution of simulated planets meet Kepler's laws while traveling around the sun, an improved approximate algorithm to calculate the optimum angle and the vertex coordinates of each planet is proposed. Using java3D perspective projection technique, the observation coordinate system is determined, and real-time viewpoint setting as well as roaming processing is realized. Through multiple view technique, we can observe the movemen
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Sharaf, M. A., A. S. Saad, and H. H. Selim. "Analytical formulations to the method of variation of parameters in terms of universal Y's functions." Serbian Astronomical Journal, no. 190 (2015): 33–40. http://dx.doi.org/10.2298/saj1590033s.

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The method of variation of parameters still has a great interest and wide applications in mathematics, physics and astrodynamics. In this paper, universal functions (the Y's functions) based on Goodyear's time transformation formula were used to establish a variation of parameters method which is useful in slightly perturbed two-body initial value problem. Moreover due to its universality, the method avoids the switching among different conic orbits which are commonly occurring in space missions. The position and velocity vectors are written in terms of f and g series. The method is developed
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Matesic, Michael R. B., Jason F. Rowe, John H. Livingston, Shishir Dholakia, Daniel Jontof-Hutter, and Jack J. Lissauer. "Gaussian Processes and Nested Sampling Applied to Kepler's Small Long-period Exoplanet Candidates." Astronomical Journal 167, no. 2 (2024): 68. http://dx.doi.org/10.3847/1538-3881/ad0fe9.

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Abstract There are more than 5000 confirmed and validated planets beyond the solar system to date, more than half of which were discovered by NASA’s Kepler mission. The catalog of Kepler’s exoplanet candidates has only been extensively analyzed under the assumption of white noise (i.i.d. Gaussian), which breaks down on timescales longer than a day due to correlated noise (point-to-point correlation) from stellar variability and instrumental effects. Statistical validation of candidate transit events becomes increasingly difficult when they are contaminated by this form of correlated noise, esp
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Qian, Zhenghong, Yaming Zhang, Dongqi Pu, Gaoyuan Xie, Die Pu, and Mingjun Ye. "A New Hybrid Improved Kepler Optimization Algorithm Based on Multi-Strategy Fusion and Its Applications." Mathematics 13, no. 3 (2025): 405. https://doi.org/10.3390/math13030405.

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The Kepler optimization algorithm (KOA) is a metaheuristic algorithm based on Kepler’s laws of planetary motion and has demonstrated outstanding performance in multiple test sets and for various optimization issues. However, the KOA is hampered by the limitations of insufficient convergence accuracy, weak global search ability, and slow convergence speed. To address these deficiencies, this paper presents a multi-strategy fusion Kepler optimization algorithm (MKOA). Firstly, the algorithm initializes the population using Good Point Set, enhancing population diversity. Secondly, Dynamic Opposit
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Claytor, Zachary R., and Jamie Tayar. "New Rotation Periods from the Kepler Bonus Background Light Curves." Astrophysical Journal 987, no. 1 (2025): 8. https://doi.org/10.3847/1538-4357/add5f0.

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Abstract The Kepler field hosts the best-studied sample of field star rotation periods. However, due to Kepler’s large 4″ pixels, many of its light curves are at high risk of contamination from background sources. The new Kepler Bonus Background light curves are deblended using a point-spread function algorithm, providing light curves of over 400,000 new background sources in addition to over 200,000 reanalyzed Kepler prime targets. These light curves provide the opportunity to search for new rotation periods. Here we apply a convolutional neural network trained on synthetic spot-modulated lig
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Zechmeister, M. "CORDIC-like method for solving Kepler’s equation." Astronomy & Astrophysics 619 (November 2018): A128. http://dx.doi.org/10.1051/0004-6361/201833162.

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Context. Many algorithms to solve Kepler’s equations require the evaluation of trigonometric or root functions. Aims. We present an algorithm to compute the eccentric anomaly and even its cosine and sine terms without usage of other transcendental functions at run-time. With slight modifications it is also applicable for the hyperbolic case. Methods. Based on the idea of CORDIC, our method requires only additions and multiplications and a short table. The table is independent of eccentricity and can be hardcoded. Its length depends on the desired precision. Results. The code is short. The conv
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Zechmeister, M. "Solving Kepler’s equation with CORDIC double iterations." Monthly Notices of the Royal Astronomical Society 500, no. 1 (2020): 109–17. http://dx.doi.org/10.1093/mnras/staa2441.

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ABSTRACT In previous work, we developed the idea to solve Kepler’s equation with a CORDIC-like algorithm, which does not require any division, but still requires multiplications in each iteration. Here we overcome this major shortcoming and solve Kepler’s equation using only bitshifts, additions and one initial multiplication. We prescale the initial vector with the eccentricity and the scale correction factor. The rotation direction is decided without correction for the changing scale. We find that double CORDIC iterations are self-correcting and compensate for possible wrong rotations in sub
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Dissertations / Theses on the topic "Kepler's Algorithm"

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"Analysis of Hardware Usage Of Shuffle Instruction Based Performance Optimization in the Blinds-II Image Quality Assessment Algorithm." Master's thesis, 2017. http://hdl.handle.net/2286/R.I.45553.

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abstract: With the advent of GPGPU, many applications are being accelerated by using CUDA programing paradigm. We are able to achieve around 10x -100x speedups by simply porting the application on to the GPU and running the parallel chunk of code on its multi cored SIMT (Single instruction multiple thread) architecture. But for optimal performance it is necessary to make sure that all the GPU resources are efficiently used, and the latencies in the application are minimized. For this, it is essential to monitor the Hardware usage of the algorithm and thus diagnose the compute and memory bottle
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Book chapters on the topic "Kepler's Algorithm"

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Ma, Haohao, and Yuxin Liao. "Multi-strategy Improved Kepler Optimization Algorithm." In Communications in Computer and Information Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-2275-4_23.

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Hales, Thomas C. "Some Algorithms Arising in the Proof of the Kepler Conjecture." In Algorithms and Combinatorics. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55566-4_22.

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Hınıslıoğlu, Yunus, Enes Kaymaz, and Uğur Güvenç. "Fitness Distance Balance Based Kepler Optimization Algorithm." In Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56322-5_10.

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Li, Jiacheng, Masato Noto, and Yang Zhang. "Improved Kepler Optimization Algorithm Based on Mixed Strategy." In Lecture Notes in Computer Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-7181-3_13.

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Dannert Tilman, Marek Andreas, and Rampp Markus. "Porting Large HPC Applications to GPU Clusters: The Codes GENE and VERTEX." In Advances in Parallel Computing. IOS Press, 2014. https://doi.org/10.3233/978-1-61499-381-0-305.

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We have developed GPU versions for two major high-performance-computing (HPC) applications originating from two different scientific domains. GENE [1,2] is a plasma microturbulence code which is employed for simulations of nuclear fusion plasmas. VERTEX [3,4,5] is a neutrino-radiation hydrodynamics code for “first principles”-simulations of core-collapse supernova explosions [6,7,8]. The codes are considered state of the art in their respective scientific domains, both concerning their scientific scope and functionality as well as the achievable compute performance, in part
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Conference papers on the topic "Kepler's Algorithm"

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Zhang, Yuzhao. "A Prediction Model for Network Information Dissemination based on Optimized Convolutional Neural Network Using Enhanced Kepler Optimization." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10722006.

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Ganesan, Annalakshmi. "Marine Mammals Sound Classification using Extreme Learning Machine with Kepler Optimization Algorithm." In 2024 5th International Conference on Smart Electronics and Communication (ICOSEC). IEEE, 2024. http://dx.doi.org/10.1109/icosec61587.2024.10722183.

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Li, Dayang, Gang Chen, Huiyu Song, Chao Deng, Lin Chen, and Guoqing Yang. "Improved Kepler Algorithm Based Maximum Power Point Tracking for Distributed Photovoltaic under Partial Shading Conditions." In 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2024. https://doi.org/10.1109/ei264398.2024.10990652.

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Xu, Hui, Zhonghao Hu, and Jiahui Chen. "A Controller Placement Approach for SDN with Cooperative Optimization Objectives Using Improved Kepler Optimization Algorithm." In 2025 28th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2025. https://doi.org/10.1109/cscwd64889.2025.11033491.

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Liu, Jiapeng, Yang Lu, Hongcheng Zhao, et al. "Ultra-Short-Term Wind Power Prediction Model Based on Kepler Optimization Algorithm Optimizing Gated Recurrent Unit Hyperparameter." In 2024 IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference (APPEEC). IEEE, 2024. https://doi.org/10.1109/appeec61255.2024.10922436.

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Pan, Tao. "Service Quality Evaluation of University Libraries based on Optimized K-means Algorithm using Modified Kepler Optimization Method." In 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). IEEE, 2024. https://doi.org/10.1109/icdscnc62492.2024.10939540.

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CONWAY, B. "An improved algorithm due to Laguerre for the solution of Kepler's equation." In 24th Aerospace Sciences Meeting. American Institute of Aeronautics and Astronautics, 1986. http://dx.doi.org/10.2514/6.1986-84.

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KLUMPP, ALLAN. "Universal Lambert and Kepler algorithms for autonomous rendezvous." In Astrodynamics Conference. American Institute of Aeronautics and Astronautics, 1990. http://dx.doi.org/10.2514/6.1990-2883.

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Yang, Shiquan, Jianqiang Dong, and Bo Yuan. "An efficient parallel ISODATA algorithm based on Kepler GPUs." In 2014 International Joint Conference on Neural Networks (IJCNN). IEEE, 2014. http://dx.doi.org/10.1109/ijcnn.2014.6889478.

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Tenenbaum, Peter, Stephen T. Bryson, Hema Chandrasekaran, et al. "An algorithm for the fitting of planet models to Kepler light curves." In SPIE Astronomical Telescopes + Instrumentation, edited by Nicole M. Radziwill and Alan Bridger. SPIE, 2010. http://dx.doi.org/10.1117/12.856705.

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