• Advances in Computational Design
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• 제4권3호
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• pp.197-210
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• 2019

Motion generation of a four-bar linkage is a type of mechanism synthesis that has a wide range of applications such as a pick-and-place operation in manufacturing. In this research, the use of meta-heuristics for motion generation of a four-bar linkage is demonstrated. Three problems of motion generation were posed as a constrained optimization probably using the weighted sum technique to handle two types of tracking errors. A simple penalty function technique was used to deal with design constraints while three meta-heuristics including differential evolution (DE), self-adaptive differential evolution (JADE) and teaching learning based optimization (TLBO) were employed to solve the problems. Comparative results and the effect of the constraint handling technique are illustrated and discussed.

• 공학교육연구
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• 제23권3호
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• pp.49-58
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• 2020

In the era of the fourth industrial revolution, the world is undergoing rapid social change. The purpose of this study is to predict the expected changes and necessary competencies and desired curriculum and teaching methods in the field of mechanical engineering in the near future. The research method was a Delphi study. It was conducted three times with 20 mechanical engineering experts. The results of the study are as follows: In the field of mechanical engineering, it will be increased the situational awareness by the use of measurement sensors, development of computer applications, flexibility and optimization by user's needs and mechanical equipment, and demand for robots equipped with AI. The mechanical engineer's career perspectives will be positive, but if it is stable, it will be a crisis. Therefore active response is needed. The competencies required in the field of mechanical engineering include collaborative skills, complex problem solving skills, self-directed learning skills, problem finding skills, creativity, communication skills, convergent thinking skills, and system engineering skills. The undergraduate curriculum to achieve above competencies includes four major dynamics, basic science, programming coding education, convergence education, data processing education, and cyber physical system education. Preferred mechanical engineering teaching methods include project-based learning, hands-on education, problem-based learning, team-based collaborative learning, experiment-based education, and software-assisted education. The mechanical engineering community and the government should be concerned about the education for mechanical engineers with the necessary competencies in the era of the 4th Industrial Revolution, which will make global competitiveness in the mechanical engineering fields.

• 한국지능시스템학회논문지
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• 제10권5호
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• pp.395-400
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• 2000

본 논문에서는 강화학습에 기반한 새로운 뉴로-퍼지 제어기를 제안한다. 시스템은 개체의 행동을 결정하는 뉴로-퍼지 제어기와 그 행동을 평가하는 동적 귀환 신경회로망으로 구성된다. 뉴로-퍼지 제어기의 후건부 소속함수는 강화학습을 한다. 한편, 유전자 알고리즘을 통하여 진화하는 동적 귀환 신경회로망은 환경으로부터 받는 외부 강화신호와 로봇의 상태로부터 내부강화 신호를 만들어낸다. 이 출력(내부강화신호)은 뉴로-퍼지 제어기의 교사신호로 사용되어 제어기가 학습을 지속하도록 만든다. 제안한 시스템은 미지의 환경에서 제어기의 최적화 및 적응에 사용할 수 있다. 제안한 알고리즘은 컴퓨터 시뮬레이션 상에서 자율 이동로봇의 장애물 회피에 적용하여 그 유효성을 확인한다.

• Structural Engineering and Mechanics
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• 제88권3호
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• pp.273-285
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• 2023

This study examines how the interaction between soil and a wind turbine's supporting system affects the optimal design. The supporting system resting on an elastic soil foundation consists of a steel conical tower and a concrete circular raft foundation, and it is subjected to wind loads. The material cost of the supporting system is aimed to be minimized employing various metaheuristic optimization algorithms including teaching-learning based optimization (TLBO). To include the influence of the soil in the optimization process, modified Vlasov and Gazetas elastic soil models are integrated into the optimization algorithms using the application programing interface (API) feature of the structural analysis program providing two-way data flow. As far as the optimal designs are considered, the best minimum cost design is achieved for the TLBO algorithm, and the modified Vlasov model makes the design economical compared with the simple Gazetas and infinitely rigid soil models. Especially, the optimum design dimensions of the raft foundation extremely reduce when the Vlasov realistic soil reactions are included in the optimum analysis. Additionally, as the designated design wind speed is decreased, the beneficial impact of soil interaction on the optimum material cost diminishes.

• Smart Structures and Systems
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• 제25권5호
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• pp.605-617
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• 2020

The existence of damages in structures causes changes in the physical properties by reducing the modal parameters. In this paper, we develop a two-stages approach based on normalized Modal Strain Energy Damage Indicator (nMSEDI) for quick applications to predict the location of damage. A two-dimensional IsoGeometric Analysis (2D-IGA), Machine Learning Algorithm (MLA) and optimization techniques are combined to create a new tool. In the first stage, we introduce a modified damage identification technique based on frequencies using nMSEDI to locate the potential of damaged elements. In the second stage, after eliminating the healthy elements, the damage index values from nMSEDI are considered as input in the damage quantification algorithm. The hybrid of Teaching-Learning-Based Optimization (TLBO) with Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) are used along with nMSEDI. The objective of TLBO is to estimate the parameters of PSO-ANN to find a good training based on actual damage and estimated damage. The IGA model is updated using experimental results based on stiffness and mass matrix using the difference between calculated and measured frequencies as objective function. The feasibility and efficiency of nMSEDI-PSO-ANN after finding the best parameters by TLBO are demonstrated through the comparison with nMSEDI-IGA for different scenarios. The result of the analyses indicates that the proposed approach can be used to determine correctly the severity of damage in beam structures.

• Geomechanics and Engineering
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• 제38권4호
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• pp.439-453
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• 2024

The research findings of two nonlinear machine learning and soft computing models- the Cuckoo optimization algorithm (COA) and the Teaching-learning-based optimization (TLBO) in combination with artificial neural network (ANN)-are presented in this article. Detailed finite element modeling (FEM) of a shallow footing on two layers of cohesionless soil provided the data sets. The models are trained and tested using the FEM outputs. Additionally, various statistical indices are used to compare and evaluate the predicted and calculated models, and the most precise model is then introduced. The most precise model is recommended to estimate the solution after the model assessment process. When the anticipated findings are compared to the FEM data, there is an excellent agreement, which indicates that the TLBO-MLP solutions in this research are reliable (R²=0.9816 for training and 0.99366 for testing). Additionally, the optimized COA-MLP network with a swarm size of 500 was observed to have R² and RMSE values of (0.9613 and 0.11459) and (0.98017 and 0.09717) for both the normalized training and testing datasets, respectively. Moreover, a straightforward formula for the soft computing model is provided, and an excellent consensus is attained, indicating a high level of dependability for the suggested model.

• Structural Engineering and Mechanics
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• 제67권6호
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• pp.617-628
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• 2018

This paper deals with the maximization of the critical buckling load of simply supported antisymmetric angle-ply plates resting on Pasternak foundation subjected to compressive loads using teaching learning based optimization method (TLBO). The first order shear deformation theory is used to obtain governing equations of the laminated plate. In the present optimization problem, the objective function is to maximize the buckling load factor and the design variables are the fibre orientation angles in the layers. Computer programming is developed in the MATLAB environment to estimate optimum stacking sequences of laminated plates. A comparison also has been performed between the TLBO, genetic algorithm (GA) and differential evolution algorithm (DE). Some examples are solved to show the applicability and usefulness of the TLBO for maximizing the buckling load of the plate via finding optimum stacking sequences of the plate. Additionally, the influences of different number of layers, plate aspect ratios, foundation parameters and load ratios on the optimal solutions are investigated.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.140-144
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• 2021

The article considers aspects of improving the quality of training of specialists based on the use of modern information and communication technologies in the educational process; the use of teaching methods and, as a result, an increase in the creative and intellectual components of educational activities; integration of various types of educational activities (educational, research, etc.); adaptation of information technology training to individual the characteristics of the student; ensuring continuity and consistency in learning; development of information technologies for distance learning; improving the software and methodological support of educational process.

• Steel and Composite Structures
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• 제52권1호
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• pp.31-43
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• 2024

A very widely used analytical method (mathematical model), mentioned in Eurocode 3, to examine the connections' bending behavior is the component-based method that has certain weak points shown in the plastic behavior part of the moment-rotation curves. In the component method available in Eurocode 3, for simplicity, the effect of strain hardening is omitted, and the bending behavior of the connection is modeled with the help of a two-line diagram. To make the component method more efficient and reliable, this research proposed its advanced version, wherein the plastic part of the diagram was developed beyond the guidelines of the mentioned Regulation, implemented to connect the end plate, and verified with the moment-rotation curves found from the laboratory model and the finite element method in ABAQUS. The findings indicated that the advanced component method (the method developed in this research) could predict the plastic part of the moment-rotation curve as well as the conventional component-based method in Eurocode 3. The comparison between the laboratory model and the outputs of the conventional and advanced component methods, as well as the outputs of the finite elements approach using ABAQUS, revealed a different percentage in the ultimate moment for bolt-extended end-plate connections. Specifically, the difference percentages were -31.56%, 2.46%, and 9.84%, respectively. Another aim of this research was to determine the optimal dimensions of the end plate joint to reduce costs without letting the mechanical constraints related to the bending moment and the resulting initial stiffness, are not compromised as well as the safety and integrity of the connection. In this research, the thickness and dimensions of the end plate and the location and diameter of the bolts were the design variables, which were optimized using Particle Swarm Optimization (PSO), Snake Optimization (SO), and Teaching Learning-Based Optimization (TLBO) to minimization the connection cost of the end plate connection. According to the results, the TLBO method yielded better solutions than others, reducing the connection costs from 43.97 to 17.45€ (60.3%), which shows the method's proper efficiency.

• Steel and Composite Structures
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• 제29권6호
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• pp.749-758
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• 2018

This article derived a hybrid coupling technique using the higher-order displacement polynomial and three soft computing techniques (teaching learning-based optimization, particle swarm optimization, and artificial bee colony) to predict the optimal stacking sequence of the layered structure and the corresponding frequency values. The higher-order displacement kinematics is adopted for the mathematical model derivation considering the necessary stress and stain continuity and the elimination of shear correction factor. A nine noded isoparametric Lagrangian element (eighty-one degrees of freedom at each node) is engaged for the discretisation and the desired model equation derived via the classical Hamilton's principle. Subsequently, three soft computing techniques are employed to predict the maximum natural frequency values corresponding to their optimum layer sequences via a suitable home-made computer code. The finite element convergence rate including the optimal solution stability is established through the iterative solutions. Further, the predicted optimal stacking sequence including the accuracy of the frequency values are verified with adequate comparison studies. Lastly, the derived hybrid models are explored further to by solving different numerical examples for the combined structural parameters (length to width ratio, length to thickness ratio and orthotropicity on frequency and layer-sequence) and the implicit behavior discuss in details.