BAS: Beetle Antennae Search Algorithm for Optimization Problems

Jiang, Xiangyuan; Li, Shuai

doi:10.5430/ijrc.v1n1p1

Cited by 357 publications

(230 citation statements)

References 13 publications

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“…BAS is a meta-heuristic algorithm that was recently proposed with a powerful performance on optimization problems. 43 It is based on the behavior of beetles using two antennae to randomly explore nearby area and tune to a higher odor concentration. A vector x t at tth time instant (t = 1, 2, · ·) represents the position of the beetle.…”

Section: Bas Architecture Tuningmentioning

confidence: 99%

Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes

Sun

Zhang

et al. 2019

Num Anal Meth Geomechanics

139

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Summary This investigation studied the coalcrete, a new supporting material produced by jet grouting (JG) for supporting surrounding coal seams. For support design, the unconfined compressive strength (UCS) of the coalcrete is an essential parameter to evaluate the jet grouting effect in coal mines. In this study, an intelligent technique was proposed for predicting the UCS of the coalcrete by combining back propagation neural network (BPNN) and beetle antennae search (BAS). The architecture of BPNN was first tuned by BAS, and then, the optimized BPNN‐BAS model was subsequently used for nonlinear relationship modeling. Several crucial influencing variables including water‐cement ratio, coal‐grout ratio, and curing time were selected as the inputs. By combining these variables, 360 coalcrete samples were prepared in a controlled laboratory environment and tested for establishing the dataset. The results demonstrate that BAS can tune the BPNN architecture more efficiently compared with random selection. Moreover, in comparison with multiple regression (MLR) and logistic regression (LR), and support vector machine (SVM), the optimized BPNN‐BAS model is more reliable and accurate for predicting coalcrete strength. Sensitivity analysis (SA) was used to obtain the variable importance, and the results demonstrate that curing time affects the UCS of the coalcrete most strongly, followed by water‐cement ratio and coal‐grout ratio. The success of this study provides an accurate and brief approach to coalcrete strength prediction.

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Section: Bas Architecture Tuningmentioning

confidence: 99%

Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes

Sun

Zhang

et al. 2019

Num Anal Meth Geomechanics

139

View full text Add to dashboard Cite

show abstract

“…Chaos theory [161] (4) Support Vector Machine(SVM) [162] (5) Genetic Algorithm(GA) [ [186] The NN model has been considered as one of the most effective theories of automatic docking [87,119], which can learn and imitate the behavior of the human brain in the execution of ship docking stage. NN algorithm and PID controller are combined to design the new controller [60,88], which can resist high wind and wave disturbance [92].…”

Section: Number Algorithm Number Algorithmmentioning

confidence: 99%

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Wang

Liu

et al. 2019

JMSE

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At present, with the development of waterborne transport vehicles, research on ship faces a new round of challenges in terms of intelligence and autonomy. The concept of maritime autonomous surface ships (MASS) has been put forward by the International Maritime Organization in 2017, in which MASS become the new focus of the waterborne transportation industry. This paper elaborates on the state-of-the-art research on motion control of MASS. Firstly, the characteristics and current research status of unmanned surface vessels in MASS and conventional ships are summarized, and the system composition of MASS is analyzed. In order to better realize the self-adaptability of the MASS motion control, the theory and algorithm of ship motion control-related systems are emphatically analyzed under the condition of classifying ship motion control. Especially, the application of intelligent algorithms in the ship control field is summarized and analyzed. Finally, this paper summarizes the challenges faced by MASS in the model establishment, motion control algorithms, and real ship experiments, and proposes the composition of MASS motion control system based on variable autonomous control strategy. Future researches on the accuracy and diversity of developments and applications to MASS motion control are suggested.

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“…The design idea is inspired by the foraging behavior of beetles in nature. By optimizing the beetle's foraging process and the concept of pheromone, an optimization algorithm with faster optimization is proposed [46].…”

Section: Problem Formulationmentioning

confidence: 99%

Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm

Chen

Wang

et al. 2019

Sensors

Self Cite

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Mobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mobile robots that can avoid both static and dynamic obstacles. The proposed intelligent optimization method can not only get a better path but also has outstanding advantages in planning time. The algorithm used in the proposed method is a hybrid algorithm based on the beetle antennae search (BAS) algorithm and the artificial potential field (APF) algorithm, termed the BAS-APF method. By establishing a potential field, the convergence speed is accelerated, and the defect that the APF is easily trapped in the local minimum value is also avoided. At the same time, by setting a security scope to make the path closer to the available path in the real environment, the effectiveness and superiority of the proposed method are verified through simulative results.

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BAS: Beetle Antennae Search Algorithm for Optimization Problems

Cited by 357 publications

References 13 publications

Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes

Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes

State-of-the-Art Research on Motion Control of Maritime Autonomous Surface Ships

Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm

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