Robust beamforming based on the worst-case performance optimization with positive semi-definite constraints by Ding-jie XU, Rui HE, Feng SHEN

“…For the robust adaptive beamforming problem of the gen l signal models, a robust beamforming algorithm based on the worst-case performance optimization with positive semi-definite constraints was proposed. …”
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PERFORMANCE PREDICTION OF ROADHEADERS USING SUPPORT VECTOR MACHINE (SVM), FIREFLY ALGORITHM (FA) AND BAT ALGORITHM (BA) by Arash Ebrahimabadi, Alireza Afradi

“…It can be concluded that while predictive models produce satisfactory results, the Bat Algorithm (BA) demonstrates a higher level of precision and realism in its outcomes.…”
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A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification by Morolake Oladayo Lawrence

“…To further improve the performance of the model, SSA was increased to select relevant features. …”
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Process Optimization for Complex Product Assembly Workshops with AGV Integration via Discrete Event Simulation by Hailong Song, Shengluo Yang, Shuoxin Yin, Zhigang Xu

“…This model simulates the coordination between AGVs and workstations while optimizing workstation layout and material flow. …”
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Transient Stability Analysis of Wind-Integrated Power Systems via a Kuramoto-like Model Incorporating Node Importance by Min Cheng, Jiawei Yu, Mingkang Wu, Yayao Zhang, Yihua Zhu, Yuanfu Zhu

“…First, virtual node technology is utilized to optimize the power grid topology model. Then an improved PageRank algorithm embedded by a critical node identification method is proposed, which simultaneously considers transmission efficiency, coupling transmission probability, and voltage influence among nodes. …”
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Improved Splitting-Integrating Methods for Image Geometric Transformations: Error Analysis and Applications by Hung-Tsai Huang, Zi-Cai Li, Yimin Wei, Ching Yee Suen

“…In this paper, we apply the improved techniques to the harmonic, Poisson and blending models, which transform the original shapes of images and patterns into arbitrary target shapes. …”
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Maintaining rockfall protection in mountain forests under climate change: optimizing management for sustainable stem size distributions by Ulrike Hiltner, Jonas Glatthorn, Timothy Thrippleton, Harald Bugmann

“…This study uses a simulation-based optimization approach, integrating the dynamic forest model ForClim with the Simulated Annealing optimization algorithm, to identify adaptive management strategies for Swiss forests. …”
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Land Use Structure Optimization in Rail Transit Station Area under TOD (Transit Oriented Development) Mode by HE Jun, WANG Junfeng, ZHANG Dongchi

“…The rationality of optimized land use structure in rail transit station area has been improved, and the the proportion of each land type has been adjusted steadily, verifying the good applicability of the model and its effectiveness for land use structure optimization in rail transit station area.…”
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Research on the Capability Maturity Evaluation of Intelligent Manufacturing Based on Firefly Algorithm, Sparrow Search Algorithm, and BP Neural Network by Li Shi, Xuehong Ding, Min Li, Yuan Liu

“…In order to overcome the shortcoming of SSA that it is easy to fall into the local optimum, the firefly disturbance strategy is introduced to improve it, a new sparrow search algorithm (FASSA) is proposed, and on this basis, an intelligent manufacturing capability maturity evaluation model based on the FASSA-BP algorithm is constructed. …”
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A novel approach for efficient resource allocation in 6G V2V networks using neighbor-aware greedy algorithm and sweep line model by Spandana Mande, Nandhakumar Ramachandran

“…The resource distribution strategy for V2V users participating in the exchange of information is based on the greedy method. The recommended algorithm determines which resource is optimal for each V2V user by taking a multi-level approach. …”
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Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification by Yunhe Zhang, Fanjun Meng, Xueguang Li, Wei Song, Dashun Zhang, Faping Zhang

“…The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. …”
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Knowledge graph-based intelligent control systems for real-time machine tool optimization by Hailong YANG, Jun YAO, Baorui DU

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Adaptive Grasp Pose Optimization for Robotic Arms Using Low-Cost Depth Sensors in Complex Environments by Aiguo Chen, Xuanfeng Li, Kerui Cen, Chitin Hon

“…Unlike traditional deep learning methods, which suffer from high data dependency and inefficiency with low-precision point clouds, the proposed approach uses ellipsoidal modeling to overcome these issues. The algorithm segments the target and then applies a three-stage optimization to refine the grasping path. …”
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Lightweight and Efficient CSI-Based Human Activity Recognition via Bayesian Optimization-Guided Architecture Search and Structured Pruning by Sungkwan Youm, Sunghyun Go

“…Motivated by the need for accuracy and efficiency in resource-constrained environments, we combine Bayesian Optimization-based Neural Architecture Search (NAS) with a structured pruning algorithm. …”
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An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection by Xiezhang Li, Guocan Feng, Jiehua Zhu

“…Numerical experiments indicate that this new algorithm makes much improvement by involving l0-norm regularization.…”
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An Adaptive Task Traffic Shaping Method for Highly Concurrent Geographic Information System Services with Limited Resources by Zheng Wu, Hongyun Zhou, Zezhao Wang, Pengda Wu, Zhaoting Ma

“…The relationship between the task arrival rate and server load is established based on the queueing theory model, and the token fill rate of the token bucket is adjusted adaptively according to resource load evaluation, so as to optimize the task processing flow. …”
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Mental Workload Detection and Assessment Through Statistical Features Extraction and Optimization Using GEL-RF Method for EEG Signals Using N-Back Dataset by Waleed Manzoor, Noman Naseer, Imran Fareed Nizami, Syed Hammad Nazeer, Husam A. Neamah

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Improving agricultural commodity allocation and market regulation: a novel hybrid model based on dual decomposition and enhanced BiLSTM for price prediction by Lihua Zhang, Fushun Wang, Fushun Wang, Kejian Wang, Kejian Wang, Zhenxue He, Zhenxue He, Chen Chen, Chen Chen, Jiahao Liu, Jiahao Liu, Chao Wang, Chao Wang, Zhe Wang

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HAMF: A Novel Hierarchical Attention-Based Multi-Modal Fusion Model for Parkinson’s Disease Classification and Severity Prediction by Anitha Rani Palakayala, P. Kuppusamy, D. Kothandaraman, Gunakala Archana, Jaideep Gera

“…This leads to richer feature extraction, besides fusing different data modalities with accurate integration. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods are used in optimizing the model, by which the convergence speed raised by 15–20 %. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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