• Magazine of the Korea Concrete Institute
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• v.2 no.2
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• pp.63-72
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• 1990

In this study, an optimization design of reinforced concrete structures is performed by using the structural optimization techniques based on the LRFD criteria. The target reliability index is estimated by the optimal reliability index considering the expected cost which is taken as a sum of the structural cost and the expected costs due to failure of the structure. The load and resistance factors calculated by using level I reliability theory with the target reliability index are compared for each load combination (D+L, D+L+w). The results of this study show that the resistance factors are ${\phi}_{M}$=0.90, ${\phi}_{V}$==0.70, ${\phi}_{C}$==0.65 and the load factors are 1.20D + 1.70L, 1.07L + 0.07L + 1.10W. The optimization techinques used to this study are S.L.P. The optimization design based on the LRFD criteria is more economical and rational than other criteria.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.176-181
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• 2001

Analysis technology is widely accepted and quite popular these days. Incorporation of the analysis result into design process is a key factor for the success of the analysis area. A few design software products have been commercialized. Generally, they are trying to make an interface between various design methods and analysis software. Optimization is a representative design method. The products are investigated and compared for the aspects of user convenience and algorithm performance. A few popular products are selected. Graphic user interface (GUI) is compared for the function and efficiency. The performances of the optimization algorithms are tested by mathematical and engineering examples. The results are discussed.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.2
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• pp.67-73
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• 2012

This paper proposes optimal maintenance strategies for power distribution systems that involve the use of the reliability-centered maintenance (RCM) method. We developed an improved decision model based on the Markov process. This model can obtain the optimal inspection interval and maintenance method based on the total expected cost. We used ordinal optimization for solving the optimal problem. Optimal maintenance strategies were presented by applying the developed method to the RBTS model. A B/C analysis proved that these strategies offer maximum benefit-to-cost.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.101-107
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• 2005

In this paper, optimized operating parameters were found using multi-dimensional engine simulation software (KIVA-3V) and micro-genetic algorithm for heavy duty diesel engine. The engine operating condition considered was at 1,737 rev/min and 57 % load. Engine simulation model was validated using an engine equipped with a high pressure electronic unit injector (HEUI) system. Three important parameters were used for the optimization - boost pressure, EGR rate and start of injection timing. Numerical optimization identified HCCI-like combustion characteristics showing significant improvements for the soot and $NO_X$ emissions. The optimized soot and $NO_X$ emissions were reduced to 0.005 g/kW-hr and 1.33 g/kW-hr, respectively. Moreover, the optimum results met EPA 2007 mandates at the operating point considered.

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1315-1320
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• 2016

The present study aims to predict the heat transfer characteristics around a square cylinder with different corner radii using multivariate adaptive regression splines (MARS). Further, the MARS-generated objective function is optimized by particle swarm optimization. The data for the prediction are taken from the recently published article by the present authors [P. Dey, A. Sarkar, A.K. Das, Development of GEP and ANN model to predict the unsteady forced convection over a cylinder, Neural Comput. Appl. (2015) 1-13]. Further, the MARS model is compared with artificial neural network and gene expression programming. It has been found that the MARS model is very efficient in predicting the heat transfer characteristics. It has also been found that MARS is more efficient than artificial neural network and gene expression programming in predicting the forced convection data, and also particle swarm optimization can efficiently optimize the heat transfer rate.

• Membrane and Water Treatment
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• v.9 no.2
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• pp.129-136
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• 2018

In this contribution, the control of multivariable reverse osmosis (RO) desalination plant using proportional-integral-derivative (PID) controllers is presented. First, feed-forward compensators are designed using simplified decoupling method and then the PID controllers are tuned for flux (flow-rate) and conductivity (salinity). The tuning of PID controllers is accomplished by minimization of the integral of squared error (ISE). The ISEs are minimized using a recently proposed algorithm named as teacher-learner-based-optimization (TLBO). TLBO algorithm is used due to being simple and being free from algorithm-specific parameters. A comparative analysis is carried out to prove the supremacy of TLBO algorithm over other state-of-art algorithms like particle swarm optimization (PSO), artificial bee colony (ABC) and differential evolution (DE). The simulation results and comparisons show that the purposed method performs better in terms of performance and can successfully be applied for tuning of PID controllers for RO desalination plants.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.116-122
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• 2023

Sentiment categorization technique be commonly isolated interested in threes significant classifications name Machine Learning Procedure (ML), Lexicon Based Method (LB) also finally, the Hybrid Method. In Machine Learning Methods (ML) utilizes phonetic highlights with apply notable ML algorithm. In this paper, in classification and identification be complete base under in optimizations technique called sequential minimal optimization with Random Forest algorithm (SMORF) for expanding the exhibition and proficiency of sentiment classification framework. The three existing classification algorithms are compared with proposed SMORF algorithm. Imitation result within experiential structure is Precisions (P), recalls (R), F-measures (F) and accuracy metric. The proposed sequential minimal optimization with Random Forest (SMORF) provides the great accuracy.

• Journal of Wetlands Research
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• v.18 no.3
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• pp.226-231
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• 2016

Land Generated Waste Load Unit(LGWLU) estimation based on land use data is required to understand the impact of land use on water quality. The method of estimating LGWLU based on the monitoring data requires a lot of time and manpower. In this study, we propose a method of land pollution unit load estimation based on land use data with LP optimization. Optimization is the process to obtain the best possible optimal solution in a given condition. This study carried out optimization by using excel solver in Microsoft Excel. This study derived LGWLU of BOD, T-N, T-P in Gongju-Si and Seocheon-Gun by using the 2012 land use map made by ministry of environment based on 2010 satellite image. This study about LGWLU estimation is expected to be able to determine more clearly the water pollution caused by land use changes.

• Food Engineering Progress
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• v.15 no.4
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• pp.297-304
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• 2011

Ramen flour formulation was optimized by applying a mixture experimental design. In the optimization, the overall palatability (OP) of cooked ramen and the rheological properties of selected dough were maximized or minimized. Blended ratios of the ingredients such as Dark Northern Spring (DNS), Hard Red Winter (HRW), and Soft White (SW) were designed on a simplex-lattice. Dough rheological properties were measured by Rapid Visco Analyser (RVA), Farinograph, and Extensograph, and the overall palatability by sensory evaluation. Several principal dough rheological properties such as RVA peak viscosity (PV), Farinograph development time (DT), and Extensograph resistance/extensibility after 45 min (R/E 45 min) were selected to influence the overall palatability by canonical correlation analysis (CCA). Goals of the optimization were given as OP maximized, PV maximized, DT minimized, and R/E at 45 min maximized. The optimization results were found to be DNS 33.3%, HRW 33.3%, and SW 33.3% with OP, 5.825; PV, 587.9 cP; DT, 3.1 min; R/E at 45 min, 2.339 BU/mm.

• Korean journal of food and cookery science
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• v.27 no.6
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• pp.691-700
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• 2011

This study's objective is to determine the optimum mixing ratio of yam (Dioscorea japonica THUMB) powder and egg for the preparation of pasta. Response surface methodology revealed 10 experimental points, including two replicates for yam powder and egg. Yam pasta formulation was optimized using rheology. Yellowness(p<0.05) and redness displayed a linear model pattern, while lightness was represented by a quadratic model. The texture(p<0.05), including flavor(p<0.05) and overall quality(p<0.05) was measured as a sensory evaluation. In addition, mechanical properties displayed significant values in adhesiveness(p<0.05). These results showed that yam powder affects flavor and appearance, and egg affects adhesiveness and overall quality. The optimum formulations processed by numerical and graphical optimization were determined at 19.50 g of yam powder and 28.07 g of egg.