Journal articles: 'Computer Optimization of Parameters'

1

Macnee, Alan B. "Computer-Aided Optimization of Transistor Model Parameters." IEEE Transactions on Education 28, no. 1 (February 1985): 4–11. http://dx.doi.org/10.1109/te.1985.4321723.

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Zhang HaiGuang, Hu QingXi, and Liu YuanYuan. "Computer Simulation and Parameters Optimization of Vacuum Casting." International Journal of Advancements in Computing Technology 5, no. 3 (February 15, 2013): 525–32. http://dx.doi.org/10.4156/ijact.vol5.issue3.61.

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Aly, Nael A. "Optimization of testability parameters." Computers & Industrial Engineering 17, no. 1-4 (January 1989): 333–39. http://dx.doi.org/10.1016/0360-8352(89)90084-3.

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Iljins, U., I. Ziemelis, H. Putāns, A. Šķēle, and J. Navickas. "Optimization of the Parameters of Solar Water Heating System." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (June 26, 2006): 353. http://dx.doi.org/10.17770/etr2003vol1.1994.

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In order to investigate the possibility to increase the efficiency of a flat-plate solar collector the mathematical model of the collector has been worked out. By solving the Laplace heat transfer equation at the boundary conditions accordingly to the construction of the collector, the obtained solution gives possibility to simulate on a computer the construction of the collector in dependence on physical, thermal and economic values of materials used for the construction. The computed results by theoretical formulas with experimental results obtained on special laboratory equipment have been compared and good concurrence acquired.

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Macnee, Alan B. "Correction to "Computer-Aided Optimization of Transistor Model Parameters''." IEEE Transactions on Education E-29, no. 1 (February 1986): 47. http://dx.doi.org/10.1109/te.1986.5570691.

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Zhao, Yu Xia, Hong Hai Xu, and De Wen Gao. "Study on Computer-Aided Optimizing Milling Parameters of Numerical Control Machine." Key Engineering Materials 419-420 (October 2009): 833–36. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.833.

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In this paper, the modern theory of milling and the optimization technique are applied to the establishment of the mathematical model of face milling to obtain the optimum face milling parameters, in which the highest productivity is the optimizing objective，and many constraints are taking into consideration．The optimization is programmed based on the complex form method and castigatory function method．And a optimization system is established, the system which is composed of optimizing calculation module, special milling parameters database and man-machine interface．And it is programmed by adopting Visual Basic．The NC milling example is optimized，the validity and practicability of optimizing mathematic model is proved，and the base of the optimization of the NC machining process is established．

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Jeang, Angus. "Robust cutting parameters optimization for production time via computer experiment." Applied Mathematical Modelling 35, no. 3 (March 2011): 1354–62. http://dx.doi.org/10.1016/j.apm.2010.09.014.

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Mallick, Zulquernain, Irfan Anjum Badruddin Magami, and Khaleed Hussain Tandur. "Operational characteristics optimization of human-computer system." IIUM Engineering Journal 8, no. 1 (September 29, 2010): 35–47. http://dx.doi.org/10.31436/iiumej.v8i1.86.

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Computer operational parameters are having vital influence on the operators efficiency from readability viewpoint. Four parameters namely font, text/background color, viewing angle and viewing distance are analyzed. The text reading task, in the form of English text, was presented on the computer screen to the participating subjects and their performance, measured in terms of number of words read per minute (NWRPM), was recorded. For the purpose of optimization, the Taguchi method is used to find the optimal parameters to maximize operators’ efficiency for performing readability task. Two levels of each parameter have been considered in this study. An orthogonal array, the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) were employed to investigate the operators’ performance/efficiency. Results showed that Times Roman font, black text on white background, 40 degree viewing angle and 60 cm viewing distance, the subjects were quite comfortable, efficient and read maximum number of words per minute. Text/background color was dominant parameter with a percentage contribution of 76.18% towards the laid down objective followed by font type at 18.17%, viewing distance 7.04% and viewing angle 0.58%. Experimental results are provided to confirm the effectiveness of this approach.

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Di Pierro, Michele, and Ron Elber. "Automated Optimization of Potential Parameters." Journal of Chemical Theory and Computation 9, no. 8 (July 5, 2013): 3311–20. http://dx.doi.org/10.1021/ct400313n.

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Fonseca, Ijar M., and Peter M. Bainum. "Integrated Structural and Control Optimization." Journal of Vibration and Control 10, no. 10 (October 2004): 1377–91. http://dx.doi.org/10.1177/1077546304042043.

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This paper focuses on the integrated structural/control optimization of a large space structure with a robot arm subject to the gravity-gradient torque through a semi-analytical approach. It is well known that the computer effort to compute numerically derivatives of the constraints with respect to design variables makes the process expensive and time-consuming. In this sense, a semi-analytical approach may represent a good alternative when optimizing systems that require sensitivity calculations with respect to design parameters. In this study, constraints from the structure and control disciplines are imposed on the optimization process with the aim of obtaining the structure’s minimum weight and the optimum control performance. In the process optimization, the sensitivity of the constraints is computed by a semi-analytical approach. This approach combines the use of analytical derivatives of the mass and stiffness matrices with the numerical solution of the eigenvalue problem to obtain the eigenvalue derivative with respect to the design variables. The analytical derivatives are easy to obtain since our space structure is a long one-dimensional beam-like spacecraft.

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Shesterikov, Alexander, Andrey Leksin, and Alexei Prokhorov. "Digital design and parameters optimization for plasmonic circuits." EPJ Web of Conferences 220 (2019): 03025. http://dx.doi.org/10.1051/epjconf/201922003025.

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The mathematical models for the CAD-platform of plasmonic circuits design have been developed. This platform provides the efficient framework for computer-aided design of semiconductor quantum dots and full-field electromagnetic simulation of surface plasmon-polariton propagation in plasmonic waveguides. The topology of an all-plasmonic devices based on graphene layers and quantum dots is proposed for the first time.

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Potente, H., and J. Natrop. "Computer-aided optimization of the parameters of heated-tool butt welding." Polymer Engineering and Science 29, no. 23 (December 1989): 1649–54. http://dx.doi.org/10.1002/pen.760292305.

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İbrahim Coşkun, M., İsmail H. Karahan, Yasin Yücel, and Teresa D. Golden. "Computer-Assisted Optimization of Electrodeposited Hydroxyapatite Coating Parameters on Medical Alloys." Metallurgical and Materials Transactions A 47, no. 4 (February 2, 2016): 1828–41. http://dx.doi.org/10.1007/s11661-016-3341-x.

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Liu, Yuanyuan, Shunguang Song, and Chunjie Wang. "Multi-objective optimization on the shock absorber design for the lunar probe using nondominated sorting genetic algorithm II." International Journal of Advanced Robotic Systems 14, no. 4 (July 1, 2017): 172988141772046. http://dx.doi.org/10.1177/1729881417720467.

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In this article, the design on the shock absorber of the lunar probe soft landing can be considered as a single- or multi-objective optimization problem. Here, the optimized objective parameters include the maximum toppling stability, defined as Dmin, and the minimum stroke of primary strut energy absorption, SPmax. However, the two optimized variables are conflict objectives. In order to give an overall consideration about the multi-performances of landing, the multi-objective optimization strategy is proposed and nondominated sorting genetic algorithm II is employed to find the best decision parameters of the shock absorber design. To conduct the optimizations, firstly, the worst landing cases and safety boundaries for both toppling and primary strut energy absorptions are obtained by the computer simulation experiments. Both single- and multi-objective optimizations are then implemented aiming to expand the stability boundary. The results show that the landing stability is effectively improved after optimizations, and also demonstrate that the multi-objective optimization strategy is superior to that of the single-objective optimization.

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Zhao, Hang, Jian Guang Li, Ying Xue Yao, and Chang Qing Liu. "Cutting Parameters Optimization for Constant Cutting Force in Milling." Applied Mechanics and Materials 10-12 (December 2007): 483–87. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.483.

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Due to cutting parameters playing an important role in machining economics and machining qualities, much attention has been paid to select optimum cutting parameters. In this paper, cutting parameters optimization for constant cutting force was discussed based-on virtual machining comprehensively. Particle swarm optimization (PSO) was used to seek for the optimal spindle speed and feed rate. The framework of virtual machining based cutting parameters optimization was established. Then two controlled experiments were conducted to demonstrate the effectiveness of cutting parameters optimization both with physical cutting and computer simulation. The results of experiments show that machining process with constant cutting force can be achieved via cutting parameters optimization based on virtual machining.

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Kazanskiy, N. L., I. S. Stepanenko, A. I. Khaimovich, S. V. Kravchenko, E. V. Byzov, and M. A. Moiseev. "Injectional multilens molding parameters optimization." Computer Optics 40, no. 2 (January 1, 2016): 203–14. http://dx.doi.org/10.18287/2412-6179-2016-40-2-203-214.

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Trontl, Krešimir, Dubravko Pevec, and Tomislav Šmuc. "Machine Learning of the Reactor Core Loading Pattern Critical Parameters." Science and Technology of Nuclear Installations 2008 (2008): 1–6. http://dx.doi.org/10.1155/2008/695153.

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The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

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Sutanto, Imam, Sri Wahjuni, Jarot Prianggono, and Sugi Guritman. "Optimization Distance Learning Computer of Network." Computer Engineering and Applications Journal 8, no. 1 (February 1, 2019): 65–76. http://dx.doi.org/10.18495/comengapp.v8i1.271.

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Implementation Distance Learning (DL) lecture at High School of Police Science namely Sekolah Tinggi Ilmu Kepolisian (STIK-PTIK) consisted of 32 Polisi Daerah (POLDA) in lecture Distance Learning (DL) throughout Indonesia. System bandwidth management using the method of simple queue, the simple queue is lacking both in bandwidth allocation. Optimization against computer networks in improving Quality of Service (QoS) using the method Per Connection Queue (PCQ) Queue Tree with four classes to model. Scale model of a priority bandwidth specifically as a model of optimization of computer networks with an average percentage of delay of 6.01%, packet loss decreased 0.26%, jitter of 13.56% and increased throughput became of 9.5%. The research is supported by the level of satisfaction by CSI towards PJJ / DL students, the methods of customer satisfaction index with the service quality (Servqual) questionnaire as against with levels of satisfaction the use of DL student participants with the result satisfaction levels of 74%. Keywords: hierarchical token bucket, per connection queue, queue tree, QoS parameters.

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Jebari, Khalid, Abdelaziz Bouroumi, and Aziz Ettouhami. "Parameters control in GAs for dynamic optimization." International Journal of Computational Intelligence Systems 6, no. 1 (February 2013): 47–63. http://dx.doi.org/10.1080/18756891.2013.754172.

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Qin Jun, Tong Xiaonian, and Yunfei Yi. "Empirical Error-based Kernel Parameters Optimization of SVM." International Journal of Advancements in Computing Technology 5, no. 7 (April 15, 2013): 852–58. http://dx.doi.org/10.4156/ijact.vol5.issue7.105.

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Yi-Cherng, Yeh, and Hsu Deh-Shiu. "Structural optimization with fuzzy parameters." Computers & Structures 37, no. 6 (January 1990): 917–24. http://dx.doi.org/10.1016/0045-7949(90)90005-m.

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Wang, Weiran, Fei Tan, Jiaxin Wu, Huilin Ge, Haifeng Wei, and Yi Zhang. "Adaptive Integral Backstepping Controller for PMSM with AWPSO Parameters Optimization." Energies 12, no. 13 (July 5, 2019): 2596. http://dx.doi.org/10.3390/en12132596.

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This article presents an adaptive integral backstepping controller (AIBC) for permanent magnet synchronous motors (PMSMs) with adaptive weight particle swarm optimization (AWPSO) parameters optimization. The integral terms of dq axis current following errors are introduced into the control law, and by constructing an appropriate Lyapunov function, the adaptive law with the differential term and the control law with the integral terms of the current error are derived to weaken the influence of internal parameters perturbation on current control. The AWPSO algorithm is used to optimize the parameters of the AIBC. Based on the analysis of single-objective optimization and multi-objective realization process, a method for transforming multi-objective optimization with convex Prato frontier into single-objective optimization is presented. By this method, a form of fitness function suitable for parameters optimization of backstepping controller is determined, and according to the theoretical derivation and large number of simulation results, the corresponding parameters of the optimization algorithm are set. By randomly adjusting the inertia weight and changing the acceleration factor, the algorithm can accelerate the convergence speed and solve the problem of parameters optimization of the AIBC. The feasibility and effectiveness of the proposed controller for PMSM are verified by simulation and experimental studies.

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Kanthima, Phannika, Pikul Puphasuk, and Tawun Remsungnen. "Intermolecular Force Field Parameters Optimization for Computer Simulations of CH4in ZIF-8." Journal of Nanotechnology 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/3926089.

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The differential evolution (DE) algorithm is applied for obtaining the optimized intermolecular interaction parameters between CH4and 2-methylimidazolate ([C4N2H5]−) using quantum binding energies of CH4-[C4N2H5]−complexes. The initial parameters and their upper/lower bounds are obtained from the general AMBER force field. The DE optimized and the AMBER parameters are then used in the molecular dynamics (MD) simulations of CH4molecules in the frameworks of ZIF-8. The results show that the DE parameters are better for representing the quantum interaction energies than the AMBER parameters. The dynamical and structural behaviors obtained from MD simulations with both sets of parameters are also of notable differences.

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Zeng, Lifang, Jianxin Hu, Dingyi Pan, and Xueming Shao. "Automated Design Optimization of a Mono Tiltrotor in Hovering and Cruising States." Energies 13, no. 5 (March 4, 2020): 1155. http://dx.doi.org/10.3390/en13051155.

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A mono tiltrotor (MTR) design which combines concepts of a tiltrotor and coaxial rotor is presented. The aerodynamic modeling of the MTR based on blade element momentum theory (BEMT) is conducted, and the method is fully validated with previous experimental data. An automated optimization approach integrating BEMT modeling and optimization algorithms is developed. Parameters such as inter-rotor spacing, blade twist, taper ratio and aspect ratio are chosen as design variables. Single-objective (in hovering or in cruising state) optimizations and multi-objective (both in hovering and cruising states) optimizations are studied at preset design points; i.e., hovering trim and cruising trim. Two single-objective optimizations result in different sets of parameter selections according to the different design objectives. The multi-objective optimization is applied to obtain an identical and compromised selection of design parameters. An optimal point is chosen from the Pareto front of the multi-objective optimization. The optimized design has a better performance in terms of the figure of merit (FM) and propulsive efficiency, which are improved by 7.3% for FM and 13.4% for propulsive efficiency from the prototype, respectively. Further aerodynamic analysis confirmed that the optimized rotor has a much more uniform load distribution along the blade span, and therefore a better aerodynamic performance in both hovering and cruising states is achieved.

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Yu, Y. X., S. D. Ke, and K. D. Jin. "Structural Parameters Optimization for a Proportional Solenoid." International Journal of Simulation Modelling 19, no. 4 (December 5, 2020): 689–700. http://dx.doi.org/10.2507/ijsimm19-4-co18.

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This paper presents an optimization method for the structural parameters of a proportional solenoid. The 3D finite element method simulation model for performance analyse of proportional solenoid was validated by force-displacement characteristic experiment. Parameter sensitivity analysis results showed that the displacement of the armature, the length of the armature, the radius of the armature, the width of the first half of the sleeve and the angle of the magnetic-isolated ring have significant effects on the electromagnetic force. Key structural parameters were optimized according to the simulation results. Experiments results showed the average electromagnetic force was increased by 20.1 % and the effective stroke was extended to 2.1 mm.

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Höglund, Albert, and Kimmo Valkealahti. "Automated optimization of key WCDMA parameters." Wireless Communications and Mobile Computing 5, no. 3 (August 23, 2004): 257–71. http://dx.doi.org/10.1002/wcm.212.

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Abbasov, Alexandr Elshanovich. "Converting three-dimensional computer geometric models for optimization of simulated devices parameters." Computer Research and Modeling 7, no. 1 (February 2015): 81–91. http://dx.doi.org/10.20537/2076-7633-2015-7-1-81-91.

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Qi, Wen Jun, Jian Jiang Fang, Yuan Yuan Zhu, and Yan Hua Huang. "Computer Aided Calculation of Welding Microstructure and Optimization of Welding Technological Parameters." Advanced Materials Research 33-37 (March 2008): 1383–88. http://dx.doi.org/10.4028/www.scientific.net/amr.33-37.1383.

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Welding Continuous Cooling Transformation (CCT) graph reflects the relationship between microstructure, hardness of steel heat-affected zone (HAZ), weld and welding cooling rate continuous cooling from high temperature, and it is the basic to select welding material, determine the optimum welding technology, relieve welding cracks and lay down standard of past heat treatment. Welding technological parameters determine welding cooling rate, and the rate determines microstructure, hardness of steel HAZ and weld, therefore we can calculate microstructure according to known welding technological parameters and optimum parameters according to wanted properties based on CCT graph. The system combines CAD and welding techniques, the welding CCT graphs are made into drawing blocks at the platform of AutoCAD, the important data of welding CCT are made into database, they are transferred and managed by Access. Based on Active Automation techniques using Visual Basic, AutoCAD graph base are transferred and data of welding CCT can be inquired and dynamically added to the base. The system has realized the prediction of welding structure and properties and optimizing welding technology.

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Relvas, C., and J. A. Simóes. "Optimization of computer numerical control set-up parameters to manufacture rapid prototypes." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 218, no. 8 (August 2004): 867–74. http://dx.doi.org/10.1243/0954405041486055.

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Hassan, A., A. EL Sherif, and K. El Barbary. "COMPUTER OPTIMIZATION OF PHASE CODED WAVEFORM PARAMETERS AND PROCESSOR FOR CLUTTER REJECTION." International Conference on Aerospace Sciences and Aviation Technology 2, CONFERENCE (April 1, 1987): 1–10. http://dx.doi.org/10.21608/asat.1987.26214.

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Tucker, R. P., A. F. Fell, J. C. Berridge, and M. W. Coleman. "Computer-Aided models for optimization of eluent parameters in chiral liquid chromatography." Chirality 4, no. 5 (1992): 316–22. http://dx.doi.org/10.1002/chir.530040510.

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MUTHURAJAN, H., R. SIVABALAN, M. TALAWAR, S. VENUGOPALAN, and B. GANDHE. "Computer code for the optimization of performance parameters of mixed explosive formulations." Journal of Hazardous Materials 136, no. 3 (August 25, 2006): 475–81. http://dx.doi.org/10.1016/j.jhazmat.2006.01.066.

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LÖSCHNER, Piotr, Krzysztof JAROSZ, and Piotr NIESŁONY. "OPTIMIZATION OF JOHNSON-COOK CONSTITUTIVE MODEL PARAMETERS." Journal of Machine Engineering 19, no. 3 (September 15, 2019): 67–74. http://dx.doi.org/10.5604/01.3001.0013.4082.

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In modern machining industry, the concept of process optimization has gained widespread recognition. FEM simulations are commonly used for the optimization of machining operations, allowing for a proper choice of tool geometry and process parameters to obtain results that are in accordance with end user criteria. However, one has to be wary that a good agreement of experimental and simulation results is mandatory if the simulation is to be used as a basis for optimization of a real-life process. Therefore, a proper choice of constitutive model parameters is vital. Those parameter values are dependent on many variables. Constitutive model parameter values are determined experimentally – therefore, they are accurate only for the conditions (temperature, strain rate etc.) under which the experiment was performed. The alteration, or optimization of model parameters is necessary if cutting and experiment conditions differ, if one wishes to obtain applicable results. In this work, the authors aim to present a method of optimizing the Johnson-Cook constitutive model parameters to obtain a better fit with experimental data.

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Li, Lin Na, and Dong Wang Zhong. "Study on the Optimizing Parameters of Underwater Drilling Blasting." Applied Mechanics and Materials 193-194 (August 2012): 614–18. http://dx.doi.org/10.4028/www.scientific.net/amm.193-194.614.

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Optimizing design of parameters is essential for the underwater blasting. The key point of optimizing model is to reflect the relation of blasting parameters, rock fragmentation and operation cost. In this paper, the blasting optimization mathematical model is established, and the optimization of the blasting parameters is obtained using the complex method with computer. Calculation results show that the blasting parameters designed by the optimizing model make the engineering cost lowest.

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Zakaria, Noor Azura, Amelia Ritahani Ismail, Nadzurah Zainal Abidin, Nur Hidayah Mohd Khalid, and Afrujaan Yakath Ali. "Optimized COCOMO parameters using hybrid particle swarm optimization." International Journal of Advances in Intelligent Informatics 7, no. 2 (April 24, 2021): 177. http://dx.doi.org/10.26555/ijain.v7i2.583.

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Software effort and cost estimation are crucial parts of software project development. It determines the budget, time, and resources needed to develop a software project. The success of a software project development depends mainly on the accuracy of software effort and cost estimation. A poor estimation will impact the result, which worsens the project management. Various software effort estimation model has been introduced to resolve this problem. COnstructive COst MOdel (COCOMO) is a well-established software project estimation model; however, it lacks accuracy in effort and cost estimation, especially for current projects. Inaccuracy and complexity in the estimated effort have made it difficult to efficiently and effectively develop software, affecting the schedule, cost, and uncertain estimation directly. In this paper, Particle Swarm Optimization (PSO) is proposed as a metaheuristics optimization method to hybrid with three traditional state-of-art techniques such as Support Vector Machine (SVM), Linear Regression (LR), and Random Forest (RF) for optimizing the parameters of COCOMO models. The proposed approach is applied to the NASA software project dataset downloaded from the promise repository. Comparing the proposed approach has been made with the three traditional algorithms; however, the obtained results confirm low accuracy before hybrid with PSO. Overall, the results showed that PSOSVM on the NASA software project dataset could improve effort estimation accuracy and outperform other models.

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Tashlinskii, A. G. "Structural optimization of pseudogradient algorithms for estimating image parameters." Pattern Recognition and Image Analysis 16, no. 2 (April 2006): 218–22. http://dx.doi.org/10.1134/s1054661806020088.

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Knypiński, Łukasz, Lech Nowak, Piotr Sujka, and Kazimierz Radziuk. "Application of a PSO algorithm for identification of the parameters of Jiles-Atherton hysteresis model." Archives of Electrical Engineering 61, no. 2 (June 1, 2012): 139–48. http://dx.doi.org/10.2478/v10171-012-0013-3.

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Application of a PSO algorithm for identification of the parameters of Jiles-Atherton hysteresis modelIn the paper an algorithm and computer code for the identification of the hysteresis parameters of the Jiles-Atherton model have been presented. For the identification the particle swarm optimization method (PSO) has been applied. In the optimization procedure five design variables has been assumed. The computer code has been elaborated using Delphi environment. Three types of material have been examined. The results of optimization have been compared to experimental ones. Selected results of the calculation for different material are presented and discussed.

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Dobe�, Josef, Martin Grabner, and Lubomir Hru�kovi�. "Identifying Model Parameters of Semiconductor Devices Using Optimization Techniques." Journal of Computing and Information Technology 15, no. 4 (2007): 331. http://dx.doi.org/10.2498/cit.1001141.

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Levin, V. I. "Ordering of Intervals and Optimization Problems with Interval Parameters." Cybernetics and Systems Analysis 40, no. 3 (May 2004): 316–24. http://dx.doi.org/10.1023/b:casa.0000041988.20251.d7.

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Groß-Vogt, Katharina, Matthias Frank, and Robert Höldrich. "Focused Audification and the optimization of its parameters." Journal on Multimodal User Interfaces 14, no. 2 (December 18, 2019): 187–98. http://dx.doi.org/10.1007/s12193-019-00317-8.

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AbstractWe present a sonification method which we call Focused Audification (FA; previously: Augmented Audification) that allows to expand pure audification in a flexible way. It is based on a combination of single-side-band modulation and a pitch modulation of the original data stream. Based on two free parameters, the sonification’s frequency range is adjustable to the human hearing range and allows to interactively zoom into the data set at any scale. The parameters have been adjusted in a multimodal experiment on cardiac data by laypeople. Following from these results we suggest a procedure for parameter optimization to achieve an optimal listening range for any data set, adjusted to human speech.

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Wang, JinFeng, XiaoLiang Fan, and Haimin Ding. "An Improved Ant Colony Optimization Approach for Optimization of Process Planning." Scientific World Journal 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/294513.

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Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.

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Huang, Zhan Jun, An Na Wang, and Cui Lei. "Research and Analysis of Discrete PID Controller Parameters’ Optimization Based on Particle Swarm Optimization Algorithm." Applied Mechanics and Materials 602-605 (August 2014): 1228–32. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1228.

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Currently, PID controllers have been widely used in industrial control. And computer control systems are widely used in the field environment. How to design a discrete PID controller which has a good control performance is very important for existing control objects. In this paper, particle swarm optimization and quadratic performance index are used to optimize the control parameters of the discrete PID controller. The optimized results are given at last. By simulation studies and analysis, the optimal parameters of the PID controller are found by particle swarm optimization algorithm, and the quadratic performance index has a good effect on optimal control.

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Silitonga, Arridina, Teuku Mahlia, Abd Shamsuddin, Hwai Ong, Jassinnee Milano, Fitranto Kusumo, Abdi Sebayang, et al. "Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization." Energies 12, no. 20 (October 9, 2019): 3811. http://dx.doi.org/10.3390/en12203811.

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Optimizing the process parameters of biodiesel production is the key to maximizing biodiesel yields. In this study, artificial neural network models integrated with ant colony optimization were developed to optimize the parameters of the two-step Cerbera manghas biodiesel production process: (1) esterification and (2) transesterification. The parameters of esterification and transesterification processes were optimized to minimize the acid value and maximize the C. manghas biodiesel yield, respectively. There was excellent agreement between the average experimental values and those predicted by the artificial neural network models, indicating their reliability. These models will be useful to predict the optimum process parameters, reducing the trial and error of conventional experimentation. The kinetic study was conducted to understand the mechanism of the transesterification process and, lastly, the model could measure the physicochemical properties of the C. manghas biodiesel.

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Isiet, Mewael, and Mohamed Gadala. "Sensitivity analysis of control parameters in particle swarm optimization." Journal of Computational Science 41 (March 2020): 101086. http://dx.doi.org/10.1016/j.jocs.2020.101086.

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Zeman, V., and Z. Hlaváč. "Optimization of parameters of torsional damping systems." Mechanism and Machine Theory 22, no. 4 (January 1987): 385–90. http://dx.doi.org/10.1016/0094-114x(87)90027-9.

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Sundar, S., and Z. Shiller. "Constrained Optimization of Multi-Degree-of-Freedom Mechanisms for Near-Time-Optimal Motions." Journal of Mechanical Design 116, no. 2 (June 1, 1994): 412–18. http://dx.doi.org/10.1115/1.2919394.

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This paper presents a method to design multi-degree-of-freedom mechanisms for near-time optimal motions. The design objective is to select system parameters, such as link lengths and actuator sizes, that will minimize the optimal motion time of the mechanism along a given path. The exact time-optimization problem is approximated by a simpler procedure that maximizes the acceleration near the end points. Representing the directions of maximum acceleration with the acceleration lines, and the reachability constraints as explicit functions of the design parameters, we transform the constrained optimization to a simpler curve-fitting procedure. This problem is formulated analytically, permitting the use of efficient gradient-based optimizations instead of the zero order optimization that is otherwise required. It is shown that with the appropriate choice of variables, the reachability constraints for planar mechanisms are linear in the design parameters. Consequently, the reachability of the entire path can be guaranteed by satisfying the reachability of only two extreme points along the path. This greatly simplifies the optimization problem since it reduces the dimensionality of the constraints and it permits the use of efficient projection methods. Examples for optimizing the dimensions of a five-bar planar mechanism demonstrate close correlation between the approximate and the exact solutions and better computational efficiency of the constrained optimization over previous penalty-based methods.

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Surace, R., S. Bruno, L. A. C. De Filippis, and A. D. Ludovico. "Multi-Objective Optimization of Aluminium Foam Manufacturing Parameters." International Journal of Simulation Modelling 8, no. 2 (June 15, 2009): 81–89. http://dx.doi.org/10.2507/ijsimm08(2)2.121.

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Kota, László, and Károly Jármai. "Improving optimization using adaptive algorithms." Pollack Periodica 16, no. 1 (March 25, 2021): 14–18. http://dx.doi.org/10.1556/606.2020.00180.

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AbstractIn the research projects and industrial projects severe optimization problems can be met, where the number of variables is high, there are a lot of constraints, and they are highly nonlinear and mostly discrete issues, where the running time can be calculated sometimes in weeks with the usual optimization methods on an average computer. In most cases in the logistics industry, the most robust constraint is the time. The optimizations are running on a typical office configuration, and the company accepts the suboptimal solution what the optimization method gives within the appropriate time limit. That is, why adaptivity is needed. The adaptivity of the optimization technique includes parameters of fine-tuning. On this way, the most sensitive setting can be found. In this article, some additional adaptive methods for logistic problems have been investigated to increase the effectivity, improve the solution in a strict time condition.

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Park, Ji Hun. "Multi-View 3D Object Reconstruction Using Coordinate Transformation." Applied Mechanics and Materials 284-287 (January 2013): 2167–70. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2167.

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The algorithm presented in this paper takes at least two images taken by an ordinary digital camera, computes camera parameters and outputs scene geometric information. The method takes at least one right-angle triangle in the scene, install a local coordinate at each triangle, and compute camera parameters by using the local coordinate transformation. The algorithm computes orientations and displacement relationships among the triangles in the scene while correcting the previously computed camera parameter values. In order to find optimal solution, we set optimization variables as camera calibration parameters and coordinate transformation values between local coordinates. The background eliminated images and calculated camera parameters allow us to reconstruct a 3D target object in VRML. The merit of this algorithm is in handling varying focal camera, in easy initial guessing value computation and in using fewer feature points compared to Zhang’s calibration method.

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Benchikhi, Loubna, Mohamed Sadgal, Aziz Elfazziki, and Fatimaezzahra Mansouri. "A Novel adaptative Discrete Cuckoo Search Algorithm for parameter optimization in computer vision." Inteligencia Artificial 20, no. 60 (October 17, 2017): 51. http://dx.doi.org/10.4114/intartif.vol20iss60pp51-71.

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Computer vision applications require choosing operators and their parameters, in order to provide the best outcomes. Often, the users quarry on expert knowledge and must experiment many combinations to find manually the best one. As performance, time and accuracy are important, it is necessary to automate parameter optimization at least for crucial operators. In this paper, a novel approach based on an adaptive discrete cuckoo search algorithm (ADCS) is proposed. It automates the process of algorithms’ setting and provides optimal parameters for vision applications. This work reconsiders a discretization problem to adapt the cuckoo search algorithm and presents the procedure of parameter optimization. Some experiments on real examples and comparisons to other metaheuristic-based approaches: particle swarm optimization (PSO), reinforcement learning (RL) and ant colony optimization (ACO) show the efficiency of this novel method.

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Journal articles on the topic 'Computer Optimization of Parameters'

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