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Biomimetics
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Biomimetic Techniques for Optimization Problems in Engineering
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Biomimetic Techniques for Optimization Problems in Engineering

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Biological Optimisation and Management".

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 13923

Special Issue Editors

Prof. Dr. Jinqi Zhu

E-Mail Website
Guest Editor
School of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China
Interests: object detection; artificial intelligence algorithm
Dr. Huiling Chen

E-Mail Website
Guest Editor
College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, China
Interests: computational intelligence; machine learning; data mining; medical diagnosis; evolutionary algorithms
Special Issues, Collections and Topics in MDPI journals
Dr. Peng Wei

E-Mail Website
Guest Editor
1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
2. Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China
Interests: signal processing; artificial intelligence algorithm
Dr. Xi Hu

E-Mail Website
Guest Editor
1. State Key Laboratory of Precision Blasting, Jianghan University, Wuhan 430056, China
2. School of Artificial Intelligence, Jianghan University, Wuhan 430056, China
Interests: systems control and optimization; meta-heuristic optimization algorithm
Dr. Chunmei Ma

E-Mail Website
Guest Editor
School of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China
Interests: object detection; artificial intelligence algorithm
Dr. Mengji Shi

E-Mail Website
Guest Editor
1. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China
2. Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province, Chengdu 611731, China
Interests: systems control and optimization; artificial intelligence algorithm

Special Issue Information

Dear Colleagues, 

Biomimetic techniques are widely applied to solve practical optimization problems in engineering. Using biomimetic techniques is one of state-of-the-art research directions in the field of intelligence optimization. In recent years, with the development of Internet technology and information science, many methods, algorithms, or systems have been designed to solve complex intelligence optimization problems.

With this Special Issue, we aim to further explore the feasibility of employing biomimetic techniques to address the broad spectrum of optimization problems in engineering. This Special Issue calls for papers with the latest research results of using these techniques to solve optimization problems in computer engineering, mechanical engineering, electronic engineering, civil engineering, material engineering, management engineering, environmental engineering, energy engineering, and education engineering.  

Prof. Dr. Jinqi Zhu
Dr. Huiling Chen
Dr. Peng Wei
Dr. Xi Hu
Dr. Chunmei Ma
Dr. Mengji Shi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomimetic techniques for optimization problems in computer engineering
  • biomimetic techniques for optimization problems in mechanical engineering
  • biomimetic techniques for optimization problems in electronic engineering
  • biomimetic techniques for optimization problems in civil engineering
  • biomimetic techniques for optimization problems in material engineering
  • biomimetic techniques for optimization problems in management engineering
  • biomimetic techniques for optimization problems in environmental engineering
  • biomimetic techniques for optimization problems in energy engineering
  • biomimetic techniques for optimization problems in education engineering

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Published Papers (7 papers)

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Research

19 pages, 2487 KiB  
Article
Vehicle Behavior Discovery and Three-Dimensional Object Detection and Tracking Based on Spatio-Temporal Dependency Knowledge and Artificial Fish Swarm Algorithm
by Yixin Chen and Qingnan Li
Biomimetics 2024, 9(7), 412; https://doi.org/10.3390/biomimetics9070412 - 6 Jul 2024
Viewed by 1324
Abstract
In complex traffic environments, 3D target tracking and detection are often occluded by various stationary and moving objects. When the target is occluded, its apparent characteristics change, resulting in a decrease in the accuracy of tracking and detection. In order to solve this [...] Read more.
In complex traffic environments, 3D target tracking and detection are often occluded by various stationary and moving objects. When the target is occluded, its apparent characteristics change, resulting in a decrease in the accuracy of tracking and detection. In order to solve this problem, we propose to learn the vehicle behavior from the driving data, predict and calibrate the vehicle trajectory, and finally use the artificial fish swarm algorithm to optimize the tracking results. The experiments show that compared with the CenterTrack method, the proposed method improves the key indicators of MOTA (Multi-Object Tracking Accuracy) in 3D object detection and tracking on the nuScenes dataset, and the frame rate is 26 fps. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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19 pages, 518 KiB  
Article
A City Shared Bike Dispatch Approach Based on Temporal Graph Convolutional Network and Genetic Algorithm
by Ji Ma, Shenggen Zheng, Shangjing Lin and Yonghong Cheng
Biomimetics 2024, 9(6), 368; https://doi.org/10.3390/biomimetics9060368 - 17 Jun 2024
Viewed by 990
Abstract
Public transportation scheduling aims to optimize the allocation of resources, enhance efficiency, and increase passenger satisfaction, all of which are crucial for building a sustainable urban transportation system. As a complement to public transportation, bike-sharing systems provide users with a solution for the [...] Read more.
Public transportation scheduling aims to optimize the allocation of resources, enhance efficiency, and increase passenger satisfaction, all of which are crucial for building a sustainable urban transportation system. As a complement to public transportation, bike-sharing systems provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, including peak usage periods in the morning and evening and significant demand fluctuations across different areas, optimizing shared bike dispatch can better meet user needs, reduce vehicle vacancy rates, and increase operating revenue. To address this issue, this article proposes a comprehensive decision-making approach for spatiotemporal demand prediction and bike dispatch optimization. For demand prediction, we design a T-GCN (Temporal Graph Convolutional Network)-based bike demand prediction model. In terms of dispatch optimization, we consider factors such as dispatch capacity, distance restrictions, and dispatch costs, and design an optimization solution based on genetic algorithms. Finally, we validate the approach using shared bike operating data and show that the T-GCN can effectively predict the short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution, verifying the model’s effectiveness. The shared bike dispatch approach proposed in this paper combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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24 pages, 6461 KiB  
Article
Maximum Power Point Tracking of Photovoltaic Generation System Using Improved Quantum-Behavior Particle Swarm Optimization
by Gwo-Ruey Yu, Yong-Dong Chang and Weng-Sheng Lee
Biomimetics 2024, 9(4), 223; https://doi.org/10.3390/biomimetics9040223 - 8 Apr 2024
Cited by 4 | Viewed by 1553
Abstract
This study introduces an improved quantum-behavior particle swarm optimization (IQPSO), tailored for the task of maximum power point tracking (MPPT) within photovoltaic generation systems (PGSs). The power stage of the MPPT system comprises a series of buck-boost converters, while the control stage contains [...] Read more.
This study introduces an improved quantum-behavior particle swarm optimization (IQPSO), tailored for the task of maximum power point tracking (MPPT) within photovoltaic generation systems (PGSs). The power stage of the MPPT system comprises a series of buck-boost converters, while the control stage contains a microprocessor executing the biomimetic algorithm. Leveraging the series buck-boost converter, the MPPT system achieves optimal operation at the maximum power point under both ideal ambient conditions and partial shade conditions (PSCs). The proposed IQPSO addresses the premature convergence issue of QPSO, enhancing tracking accuracy and reducing tracking time by estimating the maximum power point and adjusting the probability distribution. Employing exponential decay, IQPSO facilitates a reduction in tracking time, consequently enhancing convergence efficiency and search capability. Through single-peak experiments, multi-peak experiments, irradiance-changing experiments, and full-day experiments, it is demonstrated that the tracking accuracy and tracking time of IQPSO outperform existing biomimetic algorithms, such as the QPSO, firefly algorithm (FA), and PSO. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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17 pages, 41316 KiB  
Article
Design, Optimization, and Modeling of a Hydraulic Soft Robot for Chronic Total Occlusions
by Ling-Wu Meng, Xiao-Liang Xie, Xiao-Hu Zhou, Shi-Qi Liu and Zeng-Guang Hou
Biomimetics 2024, 9(3), 163; https://doi.org/10.3390/biomimetics9030163 - 6 Mar 2024
Cited by 2 | Viewed by 1599
Abstract
Chronic total occlusion (CTO) is one of the most severe and sophisticated vascular stenosis because of complete blockage, greater operation difficulty, and lower procedural success rate. This study proposes a hydraulic-driven soft robot imitating the earthworm’s locomotion to assist doctors or operators in [...] Read more.
Chronic total occlusion (CTO) is one of the most severe and sophisticated vascular stenosis because of complete blockage, greater operation difficulty, and lower procedural success rate. This study proposes a hydraulic-driven soft robot imitating the earthworm’s locomotion to assist doctors or operators in actively opening thrombi in coronary or peripheral artery vessels. Firstly, a three-actuator bionic soft robot is developed based on earthworms’ physiological structure. The soft robot’s locomotion gait inspired by the earthworm’s mechanism is designed. Secondly, the influence of structure parameters on actuator deformation, stress, and strain is explored, which can help us determine the soft actuators’ optimal structure parameters. Thirdly, the relationship between hydraulic pressure and actuator deformation is investigated by performing finite element analysis using the bidirectional fluid–structure interaction (FSI) method. The kinematic models of the soft actuators are established to provide a valuable reference for the soft actuators’ motion control. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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24 pages, 8948 KiB  
Article
Adaptive Skid-Steering Control Approach for Robots on Uncertain Inclined Planes with Redundant Load-Bearing Mobility
by Lin Zhang, Baoyu Wang, Enguang Guan, Xun Liu, Muhammad Saqib and Yanzheng Zhao
Biomimetics 2024, 9(2), 64; https://doi.org/10.3390/biomimetics9020064 - 23 Jan 2024
Cited by 3 | Viewed by 1650
Abstract
Climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components, while the motion control of climbing manipulation-oriented robots (CMo-Rs) is still challenging considering anti-slippage problems. In this study, a CMo-R with full-scenery climbing capability and redundant load-bearing mobility is [...] Read more.
Climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components, while the motion control of climbing manipulation-oriented robots (CMo-Rs) is still challenging considering anti-slippage problems. In this study, a CMo-R with full-scenery climbing capability and redundant load-bearing mobility is designed based on magnetic adsorption. A four-wheel kinematic model considering the slipping phenomenon is established. An adaptive kinematic control algorithm based on slip estimation using Lyapunov theory is designed for uncertain inclined planes. For comparison, the traditional PID-based algorithm without slip consideration is implemented as well. Numeric simulations are conducted to tackle the trajectory tracking problems for both circular and linear trajectories on the horizontal plane (HP), 50° inclined plane (50° IP), 60° inclined plane (60° IP), and vertical plane (VP). The results prove that our approach achieves better tracking accuracy. It demonstrated applicability in various climbing scenarios with uncertain inclined planes. The results of experiments also validate the feasibility, applicability, and stability of the proposed approach. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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20 pages, 9883 KiB  
Article
Simulation and Optimization Study on the Ventilation Performance of High-Rise Buildings Inspired by the White Termite Mound Chamber Structure
by Yangyang Wei, Zhiying Lin, Yihan Wang and Xinxia Wang
Biomimetics 2023, 8(8), 607; https://doi.org/10.3390/biomimetics8080607 - 14 Dec 2023
Cited by 1 | Viewed by 3667
Abstract
High-rise buildings often use mechanical systems to assist ventilation to maintain the stability of their internal environments, and the energy consumption of mechanical ventilation poses a great challenge to urban environments and energy systems. The ventilation system of termite mounds with a combination [...] Read more.
High-rise buildings often use mechanical systems to assist ventilation to maintain the stability of their internal environments, and the energy consumption of mechanical ventilation poses a great challenge to urban environments and energy systems. The ventilation system of termite mounds with a combination of internal main and attached chambers is one of the classic examples of nature’s bionic approach to maintaining a stable internal ventilation environment for large-volume structures. In this study, based on the inspiration of the internal ventilation chamber structure of bionic termite mounds, we constructed seven high-rise building chamber ventilation models based on the chamber structure of termite mounds with main chambers, main chambers plus single-attached chambers (three types), and main chambers plus double-attached chambers (three types) under natural ventilation conditions, aiming at obtaining the optimal low-energy and high-efficiency chamber ventilation model for bionic termite mounds in high-rise buildings. (1) The wind speed and wind pressure of the high-rise building with the addition of the bionic termite mound chamber structure is higher than that of the traditional chamber-free high-rise building in the sample floors, the maximal difference of the wind speed between the two models is 0.05 m/s, and the maximal difference of the wind speed of the single building is 0.14 m/s, with the maximal difference of the wind speed of the single building being 0.14 m/s; and the natural ventilation environment can be satisfied by a high-rise building with a chamber. (2) After increasing the single-attached chamber structure of the bionic termite mound, the difference in wind speed of different floors is 0.15 m/s, which is 0.10 m/s higher than that of the high-rise building model with the main chamber only. (3) Under the bionic termite mound chamber high-rise building double-attached chamber model, the maximum difference in wind speed of each floor sampling point can reach 0.19 m/s, while the wind pressure cloud map shows a stable wind environment system. (4) Two attached chambers are added at A and B of the high-rise building to form the a4 model of the chamber of the high-rise building with a double-chamber bionic termite mound. According to the results, it can be seen that the model of the nine floor sampling points of the maximum wind speed difference has six places for the highest value, and the single building wind speed difference for the minimum value of 0.10 m/s. The study aims to optimize the connectivity and ventilation performance of high-rise buildings under natural ventilation conditions and to promote the green and sustainable design of high-rise buildings. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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15 pages, 3671 KiB  
Article
Bioinspired Garra Rufa Optimization-Assisted Deep Learning Model for Object Classification on Pedestrian Walkways
by Eunmok Yang, K. Shankar, Sachin Kumar and Changho Seo
Biomimetics 2023, 8(7), 541; https://doi.org/10.3390/biomimetics8070541 - 11 Nov 2023
Cited by 1 | Viewed by 1676
Abstract
Object detection in pedestrian walkways is a crucial area of research that is widely used to improve the safety of pedestrians. It is not only challenging but also a tedious process to manually examine the labeling of abnormal actions, owing to its broad [...] Read more.
Object detection in pedestrian walkways is a crucial area of research that is widely used to improve the safety of pedestrians. It is not only challenging but also a tedious process to manually examine the labeling of abnormal actions, owing to its broad applications in video surveillance systems and the larger number of videos captured. Thus, an automatic surveillance system that identifies the anomalies has become indispensable for computer vision (CV) researcher workers. The recent advancements in deep learning (DL) algorithms have attracted wide attention for CV processes such as object detection and object classification based on supervised learning that requires labels. The current research study designs the bioinspired Garra rufa optimization-assisted deep learning model for object classification (BGRODL-OC) technique on pedestrian walkways. The objective of the BGRODL-OC technique is to recognize the presence of pedestrians and objects in the surveillance video. To achieve this goal, the BGRODL-OC technique primarily applies the GhostNet feature extractors to produce a set of feature vectors. In addition to this, the BGRODL-OC technique makes use of the GRO algorithm for hyperparameter tuning process. Finally, the object classification is performed via the attention-based long short-term memory (ALSTM) network. A wide range of experimental analysis was conducted to validate the superior performance of the BGRODL-OC technique. The experimental values established the superior performance of the BGRODL-OC algorithm over other existing approaches. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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