Application and research of mechanical design optimization based on genetic algorithm kinematics simulation technology

Bi-rong, Ding; Qu, Xin-Huai; Chen, Yuanlong

doi:10.3233/jifs-169380

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…e authors of [5,6] proposed a resampling algorithm to solve the problem of particle degradation. e authors of [7][8][9] use particle filtering algorithm to solve the damage identification problem of structural systems. Research shows that, compared with EKF algorithm, particle filtering has higher structural model parameter recognition accuracy under non-Gaussian noise conditions.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of English Speech Rationality Optimization Recognition Based on Improved Particle Filter Algorithm

Hui

2020

Complexity

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As one of the most important communication tools for human beings, English pronunciation not only conveys literal information but also conveys emotion through the change of tone. Based on the standard particle filtering algorithm, an improved auxiliary traceless particle filtering algorithm is proposed. In importance sampling, based on the latest observation information, the unscented Kalman filter method is used to calculate each particle estimate to improve the accuracy of particle nonlinear transformation estimation; during the resampling process, auxiliary factors are introduced to modify the particle weights to enrich the diversity of particles and weaken particle degradation. The improved particle filter algorithm was used for online parameter identification and compared with the standard particle filter algorithm, extended Kalman particle filter algorithm, and traceless particle filter algorithm for parameter identification accuracy and calculation efficiency. The topic model is used to extract the semantic space vector representation of English phonetic text and to sequentially predict the emotional information of different scales at the chapter level, paragraph level, and sentence level. The system has reasonable recognition ability for general speech, and the improved particle filter algorithm evaluation method is further used to optimize the defect of the English speech rationality and high recognition error rate Related experiments have verified the effectiveness of the method.

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Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of English Speech Rationality Optimization Recognition Based on Improved Particle Filter Algorithm

Hui

2020

Complexity

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“…Like the evolution process, genetic algorithm selects the operator to selects the survival of the fittest. The individuals with higher fitness are more likely to be inherited to the next generation of population, and the lower fitness individuals are less likely to be inherited to the next generation [14]. The selection operation in genetic algorithm is used to determine how to select a number of genetic operations from a parent group to the next generation group according to a certain rule.…”

Section: Selection Of Genetic Operator Of Computer Music Creation 321...mentioning

confidence: 99%

Research on music creation and audition based on wireless environment

Wang

Ming-xia

2020

J Wireless Com Network

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Traditional computer music creation is carried out through computer simulation of fixed conversion of syllables. However, there are phenomena of syllables and pitch distortions in music creation that changes rapidly in rhythm. In response to this problem, a method of music creation and sound test based on genetic algorithm and wireless network is proposed. First, the genetic algorithm is introduced to construct a general mathematical module for music creation, and genetic operators for encoding string length and group size are assigned to establish a similarity measure for computer music creation. Then, the mean cluster analysis of music creation realizes the creation of computer music. Finally, based on the wireless network technology, the sound test effect analysis of music creation was carried out. Experimental results show that the proposed method of music creation and sound test is superior to the traditional method, the accuracy of syllables is increased by 25.97%, and the accuracy of tones is increased by 34.12%. This technology can realize high-pitched music creation and audition research.

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“…Mehar et al(2015) proposed an optimal motion synthesis of a 4-bar mechanism generated by a five-precision point function and used least-squares optimization technique to minimize the structural error and improve the motion accuracy of the 4-bar mechanism. Ding et al (2018) used the advantages of nonlinear genetic algorithm to optimize the motion performance of a planar five-bar mechanism and solved the optimization problem of rod length. However, due to the complexity of the optimal solution of the parameters of the 4-bar mechanism model, the solution algorithm still suffers from insufficient convergence (2021), large errors to meet the needs of high-precision mechanisms, and poor robustness (2021) In response to the above problems, an improved artificial bee colony algorithm for studying the trajectory error of a 4-bar mechanism is proposed in this paper, which can improve the crossover rate between food sources in the learning phase, expand the population seeking space, enhance the local search ability, avoid premature convergence of genetic algorithm (Naqvi et al, 2021;Chaitanya et al, 2021;Hussain and Cheema, 2020), making the 4-bar mechanism design accuracy improved.…”

Section: Introductionmentioning

confidence: 99%

Research on mechanism dimension synthesis method of 4-bar mechanism based on improved artificial bee colony algorithm

YANG,

SUN,

ZHANG

et al. 2023

JAMDSM

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In this paper, a Genetic-Artificial Bee Colony Algorithm (G-ABCA) for mechanism optimization synthesis is proposed to improve the accuracy of the dimensional synthesis of the 4-bar mechanism. Firstly, the plane coordinate of the 4-bar mechanism was determined. Then, the relevant design parameters of the link motion were analyzed. The objective function was constructed to minimize the position error between the actual trajectory of the mechanism and the target trajectory, constraints of the 4-bar plane mechanism were added. Then, by means of the improved artificial bee colony algorithm, the length, size and angle variables of the 4-bar mechanism were optimized. The parameters of the classical case were optimized. Finally, the optimization results of the algorithm were simulated for the optimized parameters of the 4-bar mechanism. The results were compared to other optimization algorithms. The results show that the trajectory error obtained by the improved artificial bee colony algorithm is smaller and the optimization effect of the parameters of the 4-bar mechanism is better. The proposed algorithm improves the crossover rate between food sources, extends the population optimization space, improves the local search ability and prevents the premature convergence of the genetic algorithm. The validity and accuracy of the method are proved, which provides a theoretical basis for the in-depth study of the trajectory error of the 4-bar mechanism.

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Application and research of mechanical design optimization based on genetic algorithm kinematics simulation technology

Cited by 7 publications

References 13 publications

Modeling and Simulation of English Speech Rationality Optimization Recognition Based on Improved Particle Filter Algorithm

Modeling and Simulation of English Speech Rationality Optimization Recognition Based on Improved Particle Filter Algorithm

Research on music creation and audition based on wireless environment

Research on mechanism dimension synthesis method of 4-bar mechanism based on improved artificial bee colony algorithm

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