Relevant bibliographies by topics / SCA algorithm

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

Academic literature on the topic 'SCA algorithm'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "SCA algorithm"

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Zhang, Yu-Jun, Yu-Xin Yan, Juan Zhao, and Zheng-Ming Gao. "CSCAHHO: Chaotic hybridization algorithm of the Sine Cosine with Harris Hawk optimization algorithms for solving global optimization problems." PLOS ONE 17, no. 5 (2022): e0263387. http://dx.doi.org/10.1371/journal.pone.0263387.

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Because of the No Free Lunch (NFL) rule, we are still under the way developing new algorithms and improving the capabilities of the existed algorithms. Under consideration of the simple and steady convergence capability of the sine cosine algorithm (SCA) and the fast convergence rate of the Harris Hawk optimization (HHO) algorithms, we hereby propose a new hybridization algorithm of the SCA and HHO algorithm in this paper, called the CSCAHHO algorithm henceforth. The energy parameter is introduced to balance the exploration and exploitation procedure for individuals in the new swarm, and chaos
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Yang, Qingyong, Shu-Chuan Chu, Jeng-Shyang Pan, and Chien-Ming Chen. "Sine Cosine Algorithm with Multigroup and Multistrategy for Solving CVRP." Mathematical Problems in Engineering 2020 (March 27, 2020): 1–10. http://dx.doi.org/10.1155/2020/8184254.

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Sine Cosine Algorithm (SCA) has been proved to be superior to some existing traditional optimization algorithms owing to its unique optimization principle. However, there are still disadvantages such as low solution accuracy and poor global search ability. Aiming at the shortcomings of the sine cosine algorithm, a multigroup multistrategy SCA algorithm (MMSCA) is proposed in this paper. The algorithm executes multiple populations in parallel, and each population executes a different optimization strategy. Information is exchanged among populations through intergenerational communication. Using
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Tahir, Dunia, and Ramzy Ali. "Analysis of Scalability and Sensitivity for Chaotic Sine Cosine Algorithms." Iraqi Journal for Electrical and Electronic Engineering 14, no. 2 (2018): 139–54. http://dx.doi.org/10.37917/ijeee.14.2.6.

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Chaotic Sine-Cosine Algorithms (CSCAs) are new metaheuristic optimization algorithms. However, Chaotic Sine-Cosine Algorithm (CSCAs) are able to manipulate the problems in the standard Sine-Cosine Algorithm (SCA) like, slow convergence rate and falling into local solutions. This manipulation is done by changing the random parameters in the standard Sine-Cosine Algorithm (SCA) with the chaotic sequences. To verify the ability of the Chaotic Sine-Cosine Algorithms (CSCAs) for solving problems with large scale problems. The behaviors of the Chaotic Sine-Cosine Algorithms (CSCAs) were studied unde
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Parizi, Morteza Karimzadeh, Farshid Keynia, and Amid Khatibi Bardsiri. "HSCWMA: A New Hybrid SCA-WMA Algorithm for Solving Optimization Problems." International Journal of Information Technology & Decision Making 20, no. 02 (2021): 775–808. http://dx.doi.org/10.1142/s0219622021500176.

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Hybrid metaheuristic algorithms have recently become an interesting topic in solving optimization problems. The woodpecker mating algorithm (WMA) and the sine cosine algorithm (SCA) have been integrated in this paper to propose a hybrid metaheuristic algorithm for solving optimization problems called HSCWMA. Despite the high capacity of the WMA algorithm for exploration, this algorithm needs to augment exploitation especially in initial iterations. Also, the sine and cosine relations used in the SCA provide the good exploitation for this algorithm, but SCA suffers the lack of an efficient proc
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Rizk-Allah, Rizk M. "Hybridizing sine cosine algorithm with multi-orthogonal search strategy for engineering design problems." Journal of Computational Design and Engineering 5, no. 2 (2017): 249–73. http://dx.doi.org/10.1016/j.jcde.2017.08.002.

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Abstract This paper presents a new algorithm based on hybridizing the sine cosine algorithm (SCA) with a multi-orthogonal search strategy (MOSS), named multi-orthogonal sine cosine algorithm (MOSCA), for solving engineering design problems. The proposed MOSCA integrates the advantages of the SCA and MOSS to eliminate SCA's disadvantages, like unbalanced exploitation and the trapping in local optima. The proposed MOSCA works in two stages, firstly, the SCA phase starts the search process to enhance exploration capability. Secondly, the MOSS phase starts its search from SCA found so far to boost
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Rehman, Muhammad Zubair, Abdullah Khan, Rozaida Ghazali, Muhammad Aamir, and Nazri Mohd Nawi. "A new Multi Sine-Cosine algorithm for unconstrained optimization problems." PLOS ONE 16, no. 8 (2021): e0255269. http://dx.doi.org/10.1371/journal.pone.0255269.

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The Sine-Cosine algorithm (SCA) is a population-based metaheuristic algorithm utilizing sine and cosine functions to perform search. To enable the search process, SCA incorporates several search parameters. But sometimes, these parameters make the search in SCA vulnerable to local minima/maxima. To overcome this problem, a new Multi Sine-Cosine algorithm (MSCA) is proposed in this paper. MSCA utilizes multiple swarm clusters to diversify & intensify the search in-order to avoid the local minima/maxima problem. Secondly, during update MSCA also checks for better search clusters that offer c
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Song, Qi, Yourui Huang, Jiachang Xu, et al. "Research on single cell membrane algorithm and engineering application based on membrane computing theory." Journal of Physics: Conference Series 2387, no. 1 (2022): 012037. http://dx.doi.org/10.1088/1742-6596/2387/1/012037.

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Abstract Membrane computing is a new computing paradigm with great significance in the field of computer science. The Multi-membrane search algorithm (MSA) is proposed based on the membrane computational population optimization theory. It showed excellent performance in the test. This paper further studies the performance characteristics of a single individual (Single Cell Membrane Algorithm, SCA) of MSA. SCA can generate adaptive solution sets for problems of different dimensions. Through transcription and reprocessing rules, new weakly correlated feasible solutions are formed for global sear
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Jouhari, Hamza, Deming Lei, Mohammed A. A. Al-qaness, Mohamed Abd Elaziz, Ahmed A. Ewees, and Osama Farouk. "Sine-Cosine Algorithm to Enhance Simulated Annealing for Unrelated Parallel Machine Scheduling with Setup Times." Mathematics 7, no. 11 (2019): 1120. http://dx.doi.org/10.3390/math7111120.

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This paper presents a hybrid method of Simulated Annealing (SA) algorithm and Sine Cosine Algorithm (SCA) to solve unrelated parallel machine scheduling problems (UPMSPs) with sequence-dependent and machine-dependent setup times. The proposed method, called SASCA, aims to improve the SA algorithm using the SCA as a local search method. The SCA provides a good tool for the SA to avoid getting stuck in a focal point and improving the convergence to an efficient solution. SASCA algorithm is used to solve UPMSPs by minimizing makespan. To evaluate the performance of SASCA, a set of experiments wer
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Zhou, Zhiyu, Ruoxi Zhang, Jianxin Zhang, Yaming Wang, Zefei Zhu, and Chengxia Liu. "Fabric wrinkle level classification via online sequential extreme learning machine based on improved sine cosine algorithm." Textile Research Journal 90, no. 17-18 (2020): 2007–21. http://dx.doi.org/10.1177/0040517520908072.

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Because it is difficulty to classify level of fabric wrinkle, this paper proposes a fabric winkle level classification model via online sequential extreme learning machine based on improved sine cosine algorithm (SCA). The SCA has excellent global optimization ability, can explore different search spaces, and effectively avoid falling into local optimum. Because the initial population of SCA will have an impact on its optimization speed and quality, the SCA is initialized by differential evolution (DE) to avoid local optimization, and then the output weight and hidden layer bias are optimized;
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Ye, Xiaojia, Zhennao Cai, Chenglang Lu, Huiling Chen, and Zhifang Pan. "Boosted Sine Cosine Algorithm with Application to Medical Diagnosis." Computational and Mathematical Methods in Medicine 2022 (June 22, 2022): 1–21. http://dx.doi.org/10.1155/2022/6215574.

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The sine cosine algorithm (SCA) was proposed for solving optimization tasks, of which the way to obtain the optimal solution is mainly through the continuous iteration of the sine and cosine update formulas. However, SCA also faces low population diversity and stagnation of locally optimal solutions. Hence, we try to eliminate these problems by proposing an enhanced version of SCA, named ESCA_PSO. ESCA_PSO is proposed based on hybrid SCA and particle swarm optimization (PSO) by incorporating multiple mutation strategies into the original SCA_PSO. To validate the effect of ESCA_PSO in handling
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Dissertations / Theses on the topic "SCA algorithm"

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Allefeld, Carsten. "About the derivation of the SCA algorithm." Universität Potsdam, 2006. http://opus.kobv.de/ubp/volltexte/2008/2013/.

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In Allefeld & Kurths [2004], we introduced an approach to multivariate phase synchronization analysis in the form of a Synchronization Cluster Analysis (SCA). A statistical model of a synchronization cluster was described, and an abbreviated instruction on how to apply this model to empirical data was given, while an implementation of the corresponding algorithm was (and is) available from the authors. In this letter, the complete details on how the data analysis algorithm is to be derived from the model are filled in.
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Myjak, Michael D. (Michael David). "Computer Graphics Primitives and the Scan-Line Algorithm." Thesis, University of North Texas, 1988. https://digital.library.unt.edu/ark:/67531/metadc500544/.

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This paper presents the scan-line algorithm which has been implemented on the Lisp Machine. The scan-line algorithm resides beneath a library of primitive software routines which draw more fundamental objects: lines, triangles and rectangles. This routine, implemented in microcode, applies the A(BC)*D approach to word boundary alignments in order to create an extremely fast, efficient, and general purpose drawing primitive. The scan-line algorithm improves on previous methodologies by limiting the number of CPU intensive instructions and by minimizing the number of words referenced. This paper
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Dreux, M. de A. "A hybrid scan-line/ray-tracing algorithm." Thesis, Brunel University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233395.

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Agirnas, Emre. "Multi-scan Data Association Algorithm For Multitarget Tracking." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605646/index.pdf.

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Data association problem for multitarget tracking is determination of the relationship between targets and the incoming measurements from sensors of the target tracking system. Performance of a multitarget tracking system is strongly related to the chosen method for data association and target tracking algorithm. Incorrect data association effects state estimation of targets. In this thesis, we propose a new multi-scan data association algorithm for multitarget tracking systems. This algorithm was implemented by using MATLAB programming tool. Performances of the new algorithm and JPDA method f
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Freimanis, Davis, and Jonas Hongisto. "Two-Dimensional Convex Hull Algorithm Using the Iterative Orthant Scan." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208351.

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Finding the minimal convex polygon on a set of points in space is of great interest in computer graphics and data science. Furthermore, doing this efficiently is financially preferable. This thesis explores how a novel variant of bucketing, called the Iterative orthant scan, can be applied to this problem. An algorithm implementing the Iterative orthant scan was created and implemented in C++ and its real-time and asymptotic performance was compared to the industry standard algorithms along with the traditional textbook convex hull algorithm. The worst-case time complexity was shown to be a lo
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Menzerotolo, Rosa Ana. "Rain rate retrieval algorithm for Aquarius/SAC-D microwave radiometer." Master's thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4982.

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Microwave radiometers are used to measure blackbody microwave emissions emitted by natural targets. Radiative transfer theory provides a well founded physical relationship between the atmosphere and surface geophysical parameters and the brightness temperature measured by these radiometers. The atmospheric brightness temperature is proportional to the integral of the microwave absorption of water vapor, oxygen, and liquid water between the top of the atmosphere and the surface. Inverse radiative transfer models use to retrieve the water vapor, cloud liquid and oxygen content in the atmosphere
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Pomerleau, François. "Registration algorithm optimized for simultaneous localization and mapping." Mémoire, Université de Sherbrooke, 2008. http://savoirs.usherbrooke.ca/handle/11143/1465.

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Building maps within an unknown environment while keeping track of the current position is a major step to accomplish safe and autonomous robot navigation. Within the last 20 years, Simultaneous Localization And Mapping (SLAM) became a topic of great interest in robotics. The basic idea of this technique is to combine proprioceptive robot motion information with external environmental information to minimize global positioning errors. Because the robot is moving in its environment, exteroceptive data comes from different points of view and must be expressed in the same coordinate system to be
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Beattie, Robert Scott. "Side scan sonar image formation, restoration and modelling." Thesis, Robert Gordon University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318551.

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Teiller, Alexandre. "Aspects algorithmiques de l'optimisation « multistage »." Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS471.

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En optimisation combinatoire classique, étant donné une instance d’un problème, il est demandé de trouver une bonne solution réalisable. Cependant, dans de nombreux cas, les données peuvent évoluer au cours du temps et il est demandé de résoudre une séquence d’instances. Gupta et al. (2014) et Eisenstat et al. (2014) ont proposé un modèle multistage où étant donné un horizon de temps, l’entrée est une séquence d’instances (une pour chaque pas de temps), et l’objectif est de trouver une séquence de solutions (une pour chaque pas de temps) qui atteindrait un compromis entre la qualité des soluti
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Moura, Flavio dos Reis. "Detecção de clusters espacias via algoritmo scan multi-objetivo." Universidade Federal de Minas Gerais, 2006. http://hdl.handle.net/1843/RFFO-7HZHU9.

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Situations where a disease cluster does not have a regular shape are fairly common. Moreover, maps with multiple clustering, when there is not a clearly dominating primary cluster, also occur frequently. We would like to develop a method to analyze more thoroughly the severallevels of clustering that arise naturally in a disease map divided into m regions.The spatial scan statistic is the usual measure of strength of a cluster. Another important measure is its geometric regularity. A genetic multi-objective algorithm was developed elsewhere to identify irregularly shaped clusters. That method
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Books on the topic "SCA algorithm"

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Dreux, Marcelo de Andrade. A hybrid scan-line / ray-tracing algorithm. Brunel University, 1989.

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Comiso, Josefino C. SSM/I sea ice concentrations using the Bootstrap algorithm. NationalAeronautics and Space Administration, 1995.

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Comiso, Josefino C. SSM/I sea ice concentrations using the bootstrap algorithm. National Aeronautics and Space Administration, Goddard Space Flight Center, 1995.

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Andrew, Turpin, ed. Compression and coding algorithms. Kluwer Academic Publishers, 2002.

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Cavalieri, Donald J. EOS Aqua AMSR-E Sea Ice Validation Program: Meltpond2000 flight report. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Flight, Goddard Space, ed. EOS Aqua AMSR-E Sea Ice Validation Program: Meltpond2000 flight report. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Flight, Goddard Space, ed. EOS Aqua AMSR-E Sea Ice Validation Program: Meltpond2000 flight report. National Aeronautics and Space Administration, Goddard Space Flight Center, 2000.

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Yeshurun, Yehezkel. Shape description with a space variant sensor: algorithms for scan-path, fusion and convergence over multiple scans. Courant Institute of Mathematical Sciences, New York University, 1987.

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United States. National Aeronautics and Space Administration., ed. Infrared algorithm development for ocean observations with EOS-MODIS: Technical report, semiannual, July-December 1995. National Aeronautics and Space Administration, 1995.

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United States. National Aeronautics and Space Administration., ed. Infrared algorithm development for ocean observations with EOS-MODIS: Technical report, semiannual, July-December 1997. National Aeronautics and Space Administration, 1997.

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Book chapters on the topic "SCA algorithm"

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Bansal, Jagdish Chand, Prathu Bajpai, Anjali Rawat, and Atulya K. Nagar. "Sine Cosine Algorithm." In Sine Cosine Algorithm for Optimization. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9722-8_2.

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AbstractSine cosine algorithm (SCA) [1] is relatively a new algorithm, in the field of meta-heuristic algorithms. SCA is a population-based probabilistic search method that updates the position of search agents in the population using simple concept of trigonometric functions sine and cosine. SCA algorithm is inspired from the periodic property of the sine and cosine functions. The periodicity of the sine and cosine function in the range $$[-1,1]$$ provides great capacity to exploit the search space and helps in maintaining a fine balance between exploration and exploitation. In previous Chap. 1, we have already discussed about the criticality of the exploration and exploitation capabilities of any meta-heuristic algorithm.
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Bansal, Jagdish Chand, Prathu Bajpai, Anjali Rawat, and Atulya K. Nagar. "Advancements in the Sine Cosine Algorithm." In Sine Cosine Algorithm for Optimization. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9722-8_5.

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AbstractIn the last few decades, the development and advancement of meta-heuristic algorithms have become the focus of the research community as these algorithms face various challenges like, balance between exploration and exploitation, tuning of parameters, getting trapped in local optima, and very slow convergence rate. Sine cosine algorithm (SCA) also faces similar kinds of challenges and sometimes fails to perform effectively in finding the global optimal solution. Sine and cosine are trigonometric operators with a 90$$^\circ $$ phase shift from each other. The range of sine and cosine functions lies in the range $$[-1,1]$$. Sine and cosine functions in the position update equation of SCA help solutions to perform search procedure. However, in some situations, SCA promotes similar solutions in the search space, which results in the loss of diversity in the population, and the search process is susceptible to trapping in the region of local optimum [1]. Motivated by these challenges, SCA has been modified to improve its capability and efficiency in several ways. Several strategies have been employed to alter the basic version of SCA [2], aiming to enhance its effectiveness and optimization capabilities. In this chapter, we will discuss about these modifications and strategies, which have been incorporated into the sine cosine algorithm (SCA) in past few years. Apart from this, we will briefly describe the applications of the modified versions of SCA.
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Bansal, Jagdish Chand, Prathu Bajpai, Anjali Rawat, and Atulya K. Nagar. "Conclusion and Further Research Directions." In Sine Cosine Algorithm for Optimization. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9722-8_6.

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AbstractThe increasing complexity of real-world optimization problems demands fast, robust, and efficient meta-heuristic algorithms. The popularity of these intelligent techniques is gaining popularity day by day among researchers from various disciplines of science and engineering. The sine cosine algorithm is a simple population-based stochastic approach for handling different optimization problems. In this work, we have discussed the basic sine cosine algorithm for continuous optimization problems, the multi-objective sine cosine algorithm for handling multi-objective optimization problems, and the discrete (or binary) versions of sine cosine algorithm for discrete optimization problems. Sine cosine algorithm (SCA) has reportedly shown competitive results when compared to other meta-heuristic algorithms. The easy implementation and less number of parameters make the SCA algorithm, a recommended choice for performing various optimization tasks. In this present chapter, we have studied different modifications and strategies for the advancement of the sine cosine algorithm. The incorporation of concepts like opposition-based learning, quantum simulation, and hybridization with other meta-heuristic algorithms have increased the efficiency and robustness of the SCA algorithm, and meanwhile, these techniques have also increased the application spectrum of the sine cosine algorithm.
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Sarangi, Priteesha, and Prabhujit Mohapatra. "Modified Hybrid GWO-SCA Algorithm for Solving Optimization Problems." In Proceedings on International Conference on Data Analytics and Computing. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3432-4_10.

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Becerra-Rozas, Marcelo, José Lemus-Romani, Broderick Crawford, et al. "A New Learnheuristic: Binary SARSA - Sine Cosine Algorithm (BS-SCA)." In Metaheuristics and Nature Inspired Computing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94216-8_10.

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Alpirez Bock, Estuardo, Zoya Dyka, and Peter Langendoerfer. "Increasing the Robustness of the Montgomery kP-Algorithm Against SCA by Modifying Its Initialization." In Innovative Security Solutions for Information Technology and Communications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47238-6_12.

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Vali, Masoumeh, Khodakaram Salimifard, Amir H. Gandomi, and Thierry Chaussalet. "Chaotic-SCA Salp Swarm Algorithm Enhanced with Opposition Based Learning: Application to Decrease Carbon Footprint in Patient Flow." In Handbook of Nature-Inspired Optimization Algorithms: The State of the Art. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07512-4_1.

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Larsen, Casper Abild, Simon Meldahl Schmidt, Jesper Steensgaard, Anna Blume Jakobsen, Jaco van de Pol, and Andreas Pavlogiannis. "A Truly Symbolic Linear-Time Algorithm for SCC Decomposition." In Tools and Algorithms for the Construction and Analysis of Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30820-8_22.

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AbstractDecomposing a directed graph to its strongly connected components (SCCs) is a fundamental task in model checking. To deal with the state-space explosion problem, graphs are often represented symbolically using binary decision diagrams (BDDs), which have exponential compression capabilities. The theoretically-best symbolic algorithm for SCC decomposition is Gentilini et al’s $$\textsc {Skeleton}$$ S K E L E T O N algorithm, that uses O(n) symbolic steps on a graph of n nodes. However, $$\textsc {Skeleton}$$ S K E L E T O N uses $$\Theta (n)$$ Θ ( n ) symbolic objects, as opposed to (poly-)logarithmically many, which is the norm for symbolic algorithms, thereby relinquishing its symbolic nature. Here we present $$\textsc {Chain}$$ C H A I N , a new symbolic algorithm for SCC decomposition that also makes O(n) symbolic steps, but further uses logarithmic space, and is thus truly symbolic. We then extend $$\textsc {Chain}$$ C H A I N to $$\textsc {ColoredChain}$$ C O L O R E D C H A I N , an algorithm for SCC decomposition on edge-colored graphs, which arise naturally in model-checking a family of systems. Finally, we perform an experimental evaluation of $$\textsc {Chain}$$ C H A I N among other standard symbolic SCC algorithms in the literature. The results show that $$\textsc {Chain}$$ C H A I N is competitive on almost all benchmarks, and often faster, while it clearly outperforms all other algorithms on challenging inputs.
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Kao, Ming-Yang. "Atomic Scan." In Encyclopedia of Algorithms. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_41.

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Thießen, Thore, and Jan Vahrenhold. "Klee’s Measure Problem Made Oblivious." In LATIN 2022: Theoretical Informatics. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20624-5_8.

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AbstractWe study Klee’s measure problem — computing the volume of the union of n axis-parallel hyperrectangles in $$\mathbb {R}^d$$ R d — in the oblivious RAM (ORAM) setting. For this, we modify Chan’s algorithm [12] to guarantee memory access patterns and control flow independent of the input; this makes the resulting algorithm applicable to privacy-preserving computation over outsourced data and (secure) multi-party computation.For $$d = 2$$ d = 2 , we develop an oblivious version of Chan’s algorithm that runs in expected $$\mathcal {O}(n \log ^{5/3} n)$$ O ( n log 5 / 3 n ) time for perfect security or $$\mathcal {O}(n \log ^{3/2} n)$$ O ( n log 3 / 2 n ) time for computational security, thus improving over optimal general transformations. For $$d \ge 3$$ d ≥ 3 , we obtain an oblivious version with perfect security while maintaining the $$\mathcal {O}(n^{d/2})$$ O ( n d / 2 ) runtime, i. e., without any overhead.Generalizing our approach, we derive a technique to transform divide-and-conquer algorithms that rely on linear-scan processing into oblivious counterparts. As such, our results are of independent interest for geometric divide-and-conquer algorithms that maintain an order over the input. We apply our technique to two such algorithms and obtain efficient oblivious counterparts of algorithms for inversion counting and computing a closest pair in two dimensions.
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Conference papers on the topic "SCA algorithm"

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Yan, Zhiying, and Yijun Wang. "Research on Task Offloading Strategy Based on SCA Algorithm." In 2025 5th International Symposium on Computer Technology and Information Science (ISCTIS). IEEE, 2025. https://doi.org/10.1109/isctis65944.2025.11065129.

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Zhou, Fang, Yuan Gao, Xiyu Yang, and Tingting Yang. "SCA-CFAR Algorithm for Indoor Target Detection Based on LFMCW Millimeter-Wave Radar." In 2025 2nd International Conference on Digital Image Processing and Computer Applications (DIPCA). IEEE, 2025. https://doi.org/10.1109/dipca65051.2025.11042698.

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Yakupoglu, Hidayet, Haluk Gozde, M. Cengiz Taplamacioglu, and Mahir Dursun. "Sine-Cosine Algorithm (SCA) Optimized PI-Controller for Modular Multi-Level Converter Based HVDC System." In 2024 11th International Conference on Electrical and Electronics Engineering (ICEEE). IEEE, 2024. https://doi.org/10.1109/iceee62185.2024.10779236.

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Sharma, Ashutosh, Gauransh Dingwani, and Ishan Bajaj. "Interval Hessian-based Optimization Algorithm for Unconstrained Non-convex Problems." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.135173.

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Second-order optimization algorithms that leverage the exact Hessian or its approximation have been proven to achieve a faster convergence rate than first-order methods. However, their applications on training deep neural networks models, partial differential equations-based optimization problems, and large-scale non-convex problems, are hindered due to high computational cost associated with the Hessian evaluation, Hessian inversion to find the search direction, and ensuring its positive-definiteness. Accordingly, we propose a new search direction based on an interval Hessian and incorporate
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Lara-Monta�o, Oscar D., Fernando I. G�mez-Castro, Claudia Guti�rrez-Antonio, and Elena N. Dragoi. "Optimization Of Heat Exchangers Through an Enhanced Metaheuristic Strategy: The Success-Based Optimization Algorithm." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.167193.

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The optimization of shell-and-tube heat exchangers (STHEs) is critical for improving energy efficiency, reducing operational costs, and mitigating environmental impacts in industrial applications. This study evaluates the performance of the Success-Based Optimization Algorithm (SBOA), a novel metaheuristic strategy inspired by behavioral patterns in success perception, against seven established algorithms�Cuckoo Search, Differential Evolution (DE), Grey Wolf Optimization (GWO), Jaya Algorithm, Particle Swarm Optimization, Teaching-Learning Based Optimization, and Whale Optimization Algorithm�f
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Tsai, Meng-Lin, and Styliani Avraamidou. "Assessing Triviality in Random Mixed-Integer Bilevel Optimization Problems to Improve Problem Generators and Libraries." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.149474.

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While bilevel optimization is gaining prominence across various domains, the field lacks standardized tools for generating test problems that can effectively evaluate and guide the development of efficient solution algorithms. We define the term "trivial bilevel optimization problem" as a bilevel problem whose high-point relaxation solution is also feasible. These easy-to-solve problems frequently arise in na�ve implementations of random bilevel optimization problem generators, significantly impacting the evaluation of bilevel solution algorithms. However, this problem has not been addressed i
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K�ksal, Ece S., Erdal Aydin, and Metin T�rkay. "An Efficient Convex Training Algorithm for Artificial Neural Networks by Utilizing Piecewise Linear Approximations and Semi-Continuous Formulations." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.125995.

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Artificial neural networks are widely used as data-driven models for capturing complex, nonlinear systems. However, suboptimal training remains a significant challenge due to the nonlinearity of activation functions and the reliance on local solvers, which makes achieving global solutions difficult. One solution involves reformulating activation functions as piecewise linear approximations to convexify the problem, though this approach often requires substantial CPU time. This study demonstrates that a tailored branch-and-bound algorithm can effectively address these challenges by efficiently
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Eid, Maged, and Giancarlo Dalle Ave. "Automated Interpretation of Chemical Engineering Diagrams Using Computer Vision." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.129214.

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This paper presents state-of-the-art object detection and object identification algorithms for digitizing and interpreting chemical engineering diagrams, including, Block Flow Diagrams (BFDs), Process Flow Diagrams (PFDs), and Piping and Instrumentation Diagrams (P&IDs), using computer vision techniques. These diagrams are essential for visualizing plant processes and equipment but are often stored as image-based PDFs, making manual digitization/interpretation labor-intensive and error-prone. The proposed algorithm automates tasks such as detecting unit operations and identifying them usin
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Matias, Rui D. G., Alexandre F. P. Ferreira, Idelfonso B. R. Nogueira, and Ana M. Ribeiro. "A Novel AI-Driven Approach for Parameter Estimation in Gas-Phase Fixed-Bed Experiments." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.156880.

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The transition to renewable energy sources, such as biogas, requires purification processes to separate methane from carbon dioxide, with adsorption-based methods being widely employed. Accurate simulations of these systems, governed by coupled PDEs, ODEs, and algebraic equations, critically depend on precise parameter determination. While traditional approaches often result in significant errors or complex procedures, optimization algorithms provide a more efficient and reliable means of parameter estimation, simplifying the process, improving simulation accuracy, and enhancing the understand
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Wei, Yixin, Tong Qiu, and Zhen Chen. "Metabolic optimization of Vibrio natriegens based on metaheuristic algorithms and the genome-scale metabolic model." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.169411.

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In recent years, burgeoning interest in products derived from microbial production across various sectors has significantly propelled the evolution of the field of metabolic engineering. As a Gram-negative bacterium, Vibrio natriegens is characterized by its fast growth, robust metabolic capabilities, and a broad substrate spectrum, making it a promising candidate as a standard biological host for the industrial bioproduction of metabolites. Genome-scale metabolic models (GSMMs) are mathematical representations constructed based on genome annotations and gene-protein-reaction (GPR) association
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Reports on the topic "SCA algorithm"

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Eastlake, D. HMAC SHA (Hashed Message Authentication Code, Secure Hash Algorithm) TSIG Algorithm Identifiers. RFC Editor, 2006. http://dx.doi.org/10.17487/rfc4635.

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Eastlake, D., and T. Hansen. US Secure Hash Algorithms (SHA and HMAC-SHA). RFC Editor, 2006. http://dx.doi.org/10.17487/rfc4634.

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DELTA INFORMATION SYSTEMS INC HORSHAM PA. Scan Line Difference Compression Algorithm Simulation Study. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada160846.

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Eastlake, D., and T. Hansen. US Secure Hash Algorithms (SHA and SHA-based HMAC and HKDF). RFC Editor, 2011. http://dx.doi.org/10.17487/rfc6234.

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Polk, T., L. Chen, S. Turner, and P. Hoffman. Security Considerations for the SHA-0 and SHA-1 Message-Digest Algorithms. RFC Editor, 2011. http://dx.doi.org/10.17487/rfc6194.

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Chang, Shu-jen, Ray Perlner, William E. Burr, et al. Third-Round Report of the SHA-3 Cryptographic Hash Algorithm Competition. National Institute of Standards and Technology, 2012. http://dx.doi.org/10.6028/nist.ir.7896.

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Ly, Canh. Radar Array Processing of Experimental Data Via the Scan-MUSIC Algorithm. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada425842.

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Matus, Sean, and Daniel Gambill. Automation of gridded HEC-HMS model development using Python : initial condition testing and calibration applications. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/46126.

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The US Army Corps of Engineers’s (USACE) Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) rainfall-runoff model is widely used within the research community to develop both event-based and continuous rainfall-runoff models. The soil moisture accounting (SMA) algorithm is commonly used for long-term simulations. Depending on the final model setup, 12 to 18 parameters are needed to characterize the modeled watershed’s canopy, surface, soil, and routing processes, all of which are potential calibration parameters. HEC-HMS includes optimization tools to facilitate model calibrati
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Her, Shyang-Kuen. Improved I/O pad positions assignment algorithm for sea-of-gates placement. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.6200.

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Sury, O. Use of the SHA-256 Algorithm with RSA, Digital Signature Algorithm (DSA), and Elliptic Curve DSA (ECDSA) in SSHFP Resource Records. RFC Editor, 2012. http://dx.doi.org/10.17487/rfc6594.

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