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Статті в журналах з теми "GAPSOTS"

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Eliahou, Shalom, and Jean Fromentin. "Gapsets and numerical semigroups." Journal of Combinatorial Theory, Series A 169 (January 2020): 105129. http://dx.doi.org/10.1016/j.jcta.2019.105129.

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He, Liming, Jun Zhou, Sulan Dai, and Zhongliang Ma. "Influence of Combustion Modifiers on the Cure Kinetics of Glycidyl Azide Polymer Based Propellant-Evaluated through Rheo-Kinetic Approach." Polymers 11, no. 4 (April 8, 2019): 637. http://dx.doi.org/10.3390/polym11040637.

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To investigate the influence of combustion modifiers on the curing of glycidyl azide polymer spherical propellants (GAPSPs), the curing process of the GAPSPs was explored using an isothermal rheological measurement method. The parameters of cure kinetics were solved to further establish a kinetic model for the curing reaction of GAPSPs. The results showed that the curing process of GAPSPs under isothermal conditions conformed to the Kamal and LSK (Lu–Shim–Kim) models. The model data indicated significant agreement with the experimental data. The influence of four kinds of combustion performance modifiers on the curing process was explored and the results demonstrated that lead phthalate had a catalytic effect on the curing reaction of GAPSPs, whilst oxides of lead and copper, and copper adipate had no influence on the curing reaction.
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Cheldieva, F. A., T. M. Reshetnyak, A. A. Shumilova, K. S. Nurbaeva, M. V. Cherkasova, A. M. Lila, and E. L. Nasonov. "Global antiphospholipid syndrome score (GAPSS) in patients with systemic lupus erythematosus." Rheumatology Science and Practice 60, no. 5 (November 11, 2022): 546–53. http://dx.doi.org/10.47360/1995-4484-2022-546-553.

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Introduction. The Global Antiphospholipid Syndrome Score (GAPSS) is a tool proposed to quantify the risk of clinical manifestations associated with antiphospholipid antibodies (aPL) and certain cardiovascular risk factors.Objective. To validate GAPSS in a cohort of patients with systemic lupus erythematosus in Russia.Material and methods. 115 patients with SLE were included in the study, including 51 (44%) patients with systemic lupus erythematosus (SLE) with antiphospholipid syndrome (APS), 14 (12%) – SLE with aPL, and 50 (44%) – SLE.Results. There was a history of thrombosis in 58 (50%) patients with 115, of them 14 (24%) had arterial thrombosis, 29 (50%) – venous, 15 (26%) – combined. Pregnancy against the background of the disease occurred in 43 women included in the study. Of them, 29 (67%) had obstetric pathology. Patients with thrombosis and obstetric pathology had a GAPSS score of 7.17±5.64, versus 4.48±4.55 without these manifestations (p=0.0003). There was a significant association between GAPSS levels and thrombosis – patients with thrombosis had a GAPSS of 7.31±5.70, those without thrombosis – 4.00±4.81 (p=0.001). GAPPS values were higher in arterial thrombosis compared to venous thrombosis (10.40±25.30 versus 5.82±5.28; p=0.01). GAPSS levels ≥6 and ≥10 were analyzed to select GAPSS values at which a high risk of recurrent thrombosis and/or obstetric pathology could be indicated. All GAPSS levels had a significant association with clinical manifestations of APS. The quality of GAPSS by ROC analysis showed an area under the curve (AUC) for GAPSS of 0.697.Conclusion. GAPSS can be used to assess the risk of recurrence or development of thrombosis and/or obstetric pathology in patients with SLE in the Russian Federation. The GAPSS ≥6 values should be used to stratify patients with SLE into high risk group for recurrence of vascular complications. Further prospective follow-up is needed to confirm the value of GAPSS.
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LIU, YU, MINGWEI LV, and WEI ZUO. "A NEW MULTIMODAL PARTICLE SWARM OPTIMIZATION ALGORITHM BASED ON GREEDY ALGORITHM." International Journal of Computational Intelligence and Applications 11, no. 03 (September 2012): 1250020. http://dx.doi.org/10.1142/s1469026812500204.

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A new multimodal particle swarm optimization algorithm based on greedy algorithm (GAPSO) is proposed in this paper. A ring topology is employed in each niche instead of a fully connected topology in GAPSO. More importantly, GAPSO does not depend on any niching parameter, which improves its effectiveness and efficiency greatly. A range of standard test functions are employed to test this proposed algorithm's performance. Experimental results demonstrate that GAPSO performs as well as existed optimization algorithms, and needs smaller number of evaluations to locate all the global optima for simple problems. For complex problems, GAPSO can achieve better and more consistent performance, and can locate more global optima than SPSO, ANPSO and rpso, which makes it possible to be widely used in the real world.
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Cheldieva, F. A., T. M. Reshetnyak, A. A. Shumilova, K. S. Nurbaeva, M. V. Cherkasova, E. Yu Samarkina, and A. M. Lila. "Global Antiphospholipid Syndrome Score (GAPSS) in patients with primary antiphospholipid syndrome." Modern Rheumatology Journal 17, no. 1 (February 15, 2023): 31–37. http://dx.doi.org/10.14412/1996-7012-2023-1-31-37.

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Stratification of patients into groups of high and low risk of adverse outcome is necessary for timely and early prevention of the disease, as well as the selection of adequate therapy.Objective: to validate the global risk scale for the development of clinical manifestations of antiphospholipid syndrome (GAPSS) in a cohort of patients with primary antiphospholipid syndrome (PAPS).Material and methods. The study included 64 patients with PAPS. Data on clinical manifestations, traditional cardiovascular risk factors, and antiphospholipid antibody profile were collected. GAPSS values were calculated for each patient by summing the scores corresponding to risk factors as follows: 3 points – for hyperlipidemia; 1 point – for arterial hypertension; 5 points – for antibodies to cardiolipin (aCL) IgG/IgM; 4 points – for antibodies to â2-glycoprotein 1 (anti-â2GP1) IgG/IgM and 3 points – for antibodies to the phosphatidylserine-prothrombin complex (aPS/PT) IgG/IgM.Results and discussion. GAPSS indicators were comparable in women and men with PAPS – 12.0 [9.0; 13.0] points. GAPSS values did not differ in patients with thrombosis and obstetric pathology: in thrombosis they were 10.0±4.46 (range 0.0–14.0) points, in obstetric pathology – 9.26±5.08 (range 0.0–14.0) points.The localization of thrombosis did not affect the GAPSS values, which reached 9.23±5.21 points in arterial thrombosis, 10.44±4.01 points in venous thrombosis, and 10.33±4.18 points in combined ones. Patients with recurrent thrombosis had higher GAPSS scores compared to patients without relapse: 8.19±5.25 points versus 11.00±3.65 points (p=0.01). There were no significant differences in GAPSS scores in obstetric pathology at different gestational ages.GAPSS values ≥6 showed a higher risk of thrombosis recurrence: odds ratio 5.23 (95% CI 1.34–20.37). GAPSS scores ≥6 demonstrated the highest accuracy, with sensitivity and specificity of 72% and 66%, respectively. According to ROC analysis, the AUC value for GAPSS was 0.675 (95% CI 0.542–0.808; p=0.01).Conclusion. The use of GAPSS makes it possible to identify patients at increased risk of recurrent thrombosis. GAPSS scores ≥6 have high sensitivity (72%) and specificity (66%), which can be used to stratify patients with PAPS into high and low risk groups for recurrent thrombosis.
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Mustafa, Wael. "Optimization of Production Systems Using Genetic Algorithms." International Journal of Computational Intelligence and Applications 03, no. 03 (September 2003): 233–48. http://dx.doi.org/10.1142/s1469026803000987.

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This paper presents a Genetic Algorithm for Production Systems Optimization (GAPSO). The GAPSO finds an ordering of Condition Elements (CEs) in the rules of a Production System (PS) that results in a (near) optimal PS with respect to execution time. Finding such an ordering can be difficult since there is often a large number of ways to order CEs in the rules of a PS. Additionally, existing heuristics to order CEs in many cases conflict with each other. The GAPSO is applicable to PSs in general and no assumptions are made about the matching algorithm or the interpreter that executes the PS. The results of applying the GAPSO to some example PSs are presented. In all examples, the GAPSO found an optimal ordering of CEs in a small number of iterations.
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Bernardini, Matheus, and Patrick Melo. "A generalization of a theorem about gapsets with depth at most 3." Involve, a Journal of Mathematics 16, no. 2 (May 26, 2023): 313–19. http://dx.doi.org/10.2140/involve.2023.16.313.

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Nascimento, Iana Sousa, Massimo Radin, Ana Paula Rossi Gândara, Savino Sciascia, and Danieli Castro Oliveira de Andrade. "Global antiphospholipid syndrome score and anti-ß2-glycoprotein I domain I for thrombotic risk stratification in antiphospholipid syndrome: A four-year prospective study." Lupus 29, no. 7 (April 11, 2020): 676–85. http://dx.doi.org/10.1177/0961203320916527.

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Objective This study aimed to assess prospectively the role of anti-ß2-glycoprotein I domain I antibody (aß2GPI-DI) and the Global Antiphospholipid Syndrome Score (GAPSS) in identifying antiphospholipid syndrome (APS) patients at higher risk of a new event. Methods Thrombotic APS patients were followed from May 2013 to July 2017. At baseline, we measured lupus anticoagulant, IgG/IgM anticardiolipin, anti-ß2-glycoprotein I, antiphosphatidylserine-prothrombin (aPS/PT) and IgG aß2GPI-DI, and calculated GAPSS for each patient. Results A total of 44 patients (age 43 ± 10 years, 89% female, 73% primary APS) were followed for 39 months (range 9–46 months). Four new thromboses occurred, two of them after vitamin K antagonist interruption. Recurrent patients presented higher GAPSS (median 20) and were triple and aß2GPI-DI positive; non-recurrent patients had lower GAPSS (median 10.5, range 0–20) and lower ratio of triple (33%) and aß2GPI-DI positivities (38%). aß2GPI-DI was associated with higher GAPSS (median 19 vs. 7, p < 0.001; Pearson correlation 0.82, p < 0.001) and had a greater proportion of triple (83% vs. 4%, p < 0.001) and aPS/PT positivity (94% vs. 50%, p = 0.002). Conclusion Our data show a significant correlation between a validated risk score such as GAPSS and the novel antiphospholipid antibody aß2GPI-DI. Future studies are needed. However, one could speculate a role of aß2GPI-DI as a risk-stratifying tool for thrombotic events in APS.
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Zaborski, Mateusz, Michał Okulewicz, and Jacek Mańdziuk. "Analysis of statistical model-based optimization enhancements in Generalized Self-Adapting Particle Swarm Optimization framework." Foundations of Computing and Decision Sciences 45, no. 3 (September 1, 2020): 233–54. http://dx.doi.org/10.2478/fcds-2020-0013.

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AbstractThis paper presents characteristics of model-based optimization methods utilized within the Generalized Self-Adapting Particle Swarm Optimization (GA– PSO) – a hybrid global optimization framework proposed by the authors. GAPSO has been designed as a generalization of a Particle Swarm Optimization (PSO) algorithm on the foundations of a large degree of independence of individual particles. GAPSO serves as a platform for studying optimization algorithms in the context of the following research hypothesis: (1) it is possible to improve the performance of an optimization algorithm through utilization of more function samples than standard PSO sample-based memory, (2) combining specialized sampling methods (i.e. PSO, Differential Evolution, model-based optimization) will result in a better algorithm performance than using each of them separately. The inclusion of model-based enhancements resulted in the necessity of extending the GAPSO framework by means of an external samples memory - this enhanced model is referred to as M-GAPSO in the paper.We investigate the features of two model-based optimizers: one utilizing a quadratic function and the other one utilizing a polynomial function. We analyze the conditions under which those model-based approaches provide an effective sampling strategy. Proposed model-based optimizers are evaluated on the functions from the COCO BBOB benchmark set.
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Cheldieva, F. A., T. M. Reshetnyak, and A. M. Lila. "Assessment of the activity and organ damage in antiphospholipid syndrome." Modern Rheumatology Journal 15, no. 4 (August 15, 2021): 101–6. http://dx.doi.org/10.14412/1996-7012-2021-4-101-106.

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The review provides a brief description of the clinical and serological markers of antiphospholipid syndrome (APS), risk factors for the development and recurrence of thrombosis in APS. A complete description of the GAPSS and its simplified (corrected) version, adjusted GAPSS (aGAPSS), as well as the DIAPS, is presented. These scales allow one to determine the activity of APS and reflect the range of cumulative and/or irreversible damage due to the disease.
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Дисертації з теми "GAPSOTS"

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Jaax, Andrea [Verfasser]. "Der GapSet Algorithmus : Ein parallelisierbarer Algorithmus zur Berechnung minimaler Schnitte / Andrea Jaax." München : Verlag Dr. Hut, 2016. http://d-nb.info/1113335416/34.

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K, GAYATHRI DEVI. "SCHEDULING IN FLEXIBLE MANUFACTURING SYSTEM (FMS) USING SOFT COMPUTING TECHNIQUES." Thesis, 2023. http://dspace.dtu.ac.in:8080/jspui/handle/repository/20197.

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In today's highly competitive and fast-paced manufacturing industry, companies are increasingly turning to flexible manufacturing systems (FMS) to improve their efficiency and productivity. FMS is an automated manufacturing system that includes transport vehicles, automated storage, and a comprehensive computer control system, all working together to produce a wide variety of parts quickly and efficiently. FMS is a critical component of Industry 4.0, the fourth industrial revolution characterized by the integration of advanced technologies making it smart manufacturing process. Scheduling optimization is a crucial aspect of Flexible Manufacturing Systems (FMS) that involves determining the optimal sequence for producing multiple components and allocating the appropriate resources to each operation. The FMS scheduling optimization is of paramount importance for manufacturers, as it results in increased productivity and reduced production costs. By utilizing an efficient FMS scheduling optimization, manufacturers can achieve faster production times, higher throughput rates, and improved quality control. The optimization of FMS scheduling is a significant factor in the current Industry 4.0. The integration of advanced technologies with FMS scheduling optimization can lead to the development of smarter factories with improved efficiency, accuracy, and automation. As such, the optimization of FMS scheduling is a vital element in the success of modern manufacturing operations. Traditional optimization methods, such as linear programming and dynamic programming, have been used for scheduling optimization in manufacturing for several decades. However, these methods have limitations when it comes to solving complex scheduling problems in Flexible Manufacturing Systems (FMS), which are characterized by large vii search spaces, non-linear relationships, and combinatorial constraints. Metaheuristics, a class of optimization algorithms that use heuristic rules to explore the search space efficiently, have emerged as a powerful tool for solving complex FMS scheduling problems. Metaheuristic algorithms are inspired from natural phenomena and mimics it to find near-optimal solutions by iteratively exploring the search space, making probabilistic moves, and adapting to the search environment. These algorithms can handle multiple objectives, constraints, and uncertainty, making them suitable for FMS scheduling optimization. With the advancement of computing power and the availability of high performance computing platforms, metaheuristic algorithms have become even more useful in FMS scheduling optimization. In this research, three novel hybrid meta heuristic methods have been proposed: 1) GAPSOTS- An amalgamation of Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Tabu Search (TS) 2) HAdFA- The Hybrid Adaptive Firefly Algorithm and 3) HFPA- Hybrid Flower Pollination Algorithm. GAPSOTS is simple hybridization of classic meta heuristics without any adaptive features. The GAPSOTS suffered from local optima entrapment and convergence was impetuous. To address the premature convergence problem inherent in the classic Firefly Algorithm (FA), the researcher developed HAdFA that employs two novel adaptive strategies: employing an adaptive randomization parameter (α), which dynamically modifies at each step, and Gray relational analysis updates firefly at each step, thereby maintaining a balance between diversification and intensification. HFPA is inspired by the pollination strategy of flowers. Additionally, both HAdFA and HFPA are incorporated with a local search technique of enhanced simulated annealing to accelerate the algorithm and prevent local optima entrapment. viii The current study addresses FMS scheduling optimization for the following: • A Flexible Job Shop Scheduling Problem (FJSSP) was analysed, studied and tested with proposed meta-heuristics for several benchmark problems for multi-objectives of makespan (MSmax), maximal machine workload (WLmax), total workload (WLtotal), total idle time (Tidle ) and Total tardiness, i.e., lateness of jobs (Tlate ). • An FMS configuration, integrated with AGVs, Automatic storage and retrieval system (AS/RS) has been optimized using a Combined Objective Function (COF) with the aim of minimizing the machine idle time and the total penalty cost combinedly. In order to test the effectiveness of this optimization method, several problems were developed and tested by varying the number of jobs and machines for this particular FMS setup. • The concurrent scheduling of machines and AGVs in a multi-machine FMS setup for different layouts has been studied. This problem has been developed as a multi objective optimization with objectives to minimize the makespan, mean flow time, and mean machine idle time. Proposed meta-heuristics have been employed and tested on randomly generated example problems to evaluate their performance for this setup. These meta-heuristics have proven to be effective in finding optimal solutions, and their application can lead to improved efficiency and reduced costs in FMS setups. • Finally, a real-life case study was conducted in a Lube Oil Blending Plant, Faridabad, India. The proposed GAPSOTS and HAdFA are tested for three problems with varying jobs and machines for multi objectives. ix The corresponding computational experiments have been reported and analyzed. The suggested algorithms have been implemented and tested using Matlab R2019a, computing environment on an Intel Core™i7, with Windows 10. The results indicate that the proposed HAdFA tends to be more efficient among the proposed algorithms and consistently demonstrated to achieve not only optimal solutions but also new makespan values were found for some problems. The efficiency of HAdFA can be attributed to the adaptive parameters integrated into it. This algorithm significantly improves convergence speed and enables the exploration of a large number of rich optimal solutions.
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Deacon, Johan Abraham. "Drywingselektroniese mutators met siklies-resonante gapsers en hekafskakelbare tiristors." Thesis, 2014. http://hdl.handle.net/10210/12202.

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M.Ing. (Electrical & Electronic Engineering)
The gate turn-off thyristor is discussed as a power switch. A gate-firing circuit for gate turn-off thyristors in the range 10 A - 300 A was developed. The resonant dc-link as snubber for voltage fed inverters is discussed. On considering various factors, the gate turn-off thyristor was chosen as switching component in the inverter. The problems that deve16ped with the use of gate turn-off thyristors in resonant dc-link inverters w,re discussed. Which lead to the development of a storage time compensator for gate turn-off thyristors. Attention was given to the various possible control methods for the resonant dc-link. A study of the possible control strategies results in the development and manufacturing of both a single-phase and a three-phase controller. The operation of the resonant inverter and inverter/load system were evaluated in terms of wave shapes in the time domain.
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Книги з теми "GAPSOTS"

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New York Times and Galison. New York Times Gapstow Bridge Boxed Holiday Full Notecards. Galison, 2014.

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Частини книг з теми "GAPSOTS"

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Eliahou, Shalom, and Jean Fromentin. "Gapsets of Small Multiplicity." In Numerical Semigroups, 63–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40822-0_5.

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Huo, Tieqiao, Junxi Zhang, and Xiaojun Wu. "Cluster Analysis Based on GAPSO Evolutionary Algorithm." In Communications in Computer and Information Science, 207–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24282-3_28.

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Chen, Yifan, Feng Qiao, Lingzhong Guo, and Tao Liu. "GAPSO-Based Traffic Signal Control in Isolated Intersection with Multiple Objectives." In Advances in Intelligent Systems and Computing, 263–75. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4575-1_26.

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Pârvulescu, V. I., M. Alifanti, M. H. Zahedi-Niaki, P. Grange, and S. Kaliaguine. "A comparison of SAPO, GaPSO, MgAPO and GaPO's as DeNOx catalysts." In Studies in Surface Science and Catalysis, 823–30. Elsevier, 2002. http://dx.doi.org/10.1016/s0167-2991(02)80107-0.

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Тези доповідей конференцій з теми "GAPSOTS"

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Barton, Carl, Tomáš Flouri, Costas S. Iliopoulos, and Solon P. Pissis. "GapsMis." In BCB'13: ACM-BCB2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2506583.2506584.

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Yuan, Wenqiang, and Yusheng Liu. "Geometry-Based PSO for Mechatronic System Design Optimization." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-62545.

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In this work, we present a new multi-objective particle swarm optimization algorithm (PSO) characterized by the use of the geometrization analysis of the particles. The proposed method, called geometry analysis PSO (GAPSO), firstly parameterize the data points of the optimization model of mechatronic system to obtain their parameter values, then one curve or one surface is adopted to fit these points and the tangent value and normal value for each point are acquired, eventually the particles are guided by the use of its derivative value and tangent value to approximate the true Pareto front and get a uniform distribution. Our proposed method is compared with respect to two multi-objective metaheuristics representative of the state-of-the-art in this area. The experiments carried out indicate that GAPSO obtains remarkable results in terms of both accuracy and distribution.
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Wu, Xiaojun, Ying Wang, and Tiantian Zhang. "An Improved GAPSO Hybrid Programming Algorithm." In 2009 International Conference on Information Engineering and Computer Science. IEEE, 2009. http://dx.doi.org/10.1109/iciecs.2009.5365983.

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Das, Angan, and Ranga Vemuri. "GAPSYS: A GA-based Tool for Automated Passive Analog Circuit Synthesis." In 2007 IEEE International Symposium on Circuits and Systems. IEEE, 2007. http://dx.doi.org/10.1109/iscas.2007.378519.

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Peng, Junqiang, and Ruige Liu. "Research on EEG signal emotion recognition based on improved GAPSO-SVM." In 2023 IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA). IEEE, 2023. http://dx.doi.org/10.1109/eebda56825.2023.10090851.

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DING, Yuanming, Chengyang LIU, Qian LU, and Min ZHU. "Effectiveness Evaluation of UUV Cooperative Combat Based on GAPSO-BP Neural Network." In 2019 Chinese Control And Decision Conference (CCDC). IEEE, 2019. http://dx.doi.org/10.1109/ccdc.2019.8833162.

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Jahwar, Alan Fuad, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree, Dilovan Asaad Zebari, and Falah Y. H. Ahmed. "An Integrated Gapso Approach for Solving Problem of an Examination Timetabiking System." In 2021 IEEE Symposium on Industrial Electronics & Applications (ISIEA). IEEE, 2021. http://dx.doi.org/10.1109/isiea51897.2021.9509984.

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Parizi Nejad, Zahra, and Vahid Sattari Naeini. "Application of feature selection to data fusion based on improved perceptron and GAPSO." In 2014 6th Conference on Information and Knowledge Technology (IKT). IEEE, 2014. http://dx.doi.org/10.1109/ikt.2014.7030338.

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Lin, Xiaoli, and Xiaolong Zhang. "Protein folding structure optimization based on GAPSO algorithm in the off-lattice model." In 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2014. http://dx.doi.org/10.1109/bibm.2014.6999246.

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Li, Ziyu, Shenghua Dai, Ziyuan Zheng, and Yao Liang. "Fault Diagnosis of ZD6 Turnout System Based on Wavelet Transform and GAPSO-FCM." In 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). IEEE, 2021. http://dx.doi.org/10.1109/itsc48978.2021.9565075.

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