RE-YOLO: An apple picking detection algorithm fusing receptive-field attention convolution and efficient multi-scale attention. by Jinxue Sui, Li Liu, Zuoxun Wang, Li Yang

“…The widespread cultivation of apples highlights the importance of efficient and accurate apple detection algorithms in robotic picking technology. The accuracy of current apple picking detection algorithms is still limited when the distribution is dense and occlusion exists, and there is a significant challenge in deploying current high accuracy detection models on edge devices with limited computational resources. …”
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Accurate estimation of CO2 adsorption on activated carbon with multi-layer feed-forward neural network (MLFNN) algorithm by Alireza Rostami, Mohammad Amin Anbaz, Hamid Reza Erfani Gahrooei, Milad Arabloo, Alireza Bahadori

“…The adsorption equilibrium data for carbon dioxide were predicted with two commonly used isotherm models in order to compare with multi-layer feed-forward neural network (MLFNN) algorithm for a wide range of partial pressure. As a result, the ANN-based algorithm shows much better efficiency and accuracy than the Sips and Langmuir isotherms. …”
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A Variable Selection Method Based on Fast Nondominated Sorting Genetic Algorithm for Qualitative Discrimination of Near Infrared Spectroscopy by Hubin Liu, Na Liu, Yuhui Yuan, Cihai Zhang, Longlian Zhao, Junhui Li

“…A variable selection method based on a fast nondominated-ranking genetic algorithm (NSGA-II) was proposed in this paper for qualitative discrimination of NIR spectra. …”
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iFQS: An Integrated FCNP-Q-Learning-Based Scheduling Algorithm for On-Demand Charging in Wireless Rechargeable Sensor Networks by Man Gun Ri, Chun Hyok Kim, Se Hun Pak, Chol Min Pong

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Distribution Network Reconfiguration Using Selective Firefly Algorithm and a Load Flow Analysis Criterion for Reducing the Search Space by Cassio Gerez, Lindenberg I. Silva, Edmarcio A. Belati, Alfeu J. Sguarezi Filho, Eduardo C. M. Costa

“…Results found for simulations with 33, 70, and 84 buses are presented and comparisons with selective particle swarm optimization (SPSO) and selective bat algorithm (SBAT) are made.…”
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Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

“…Moreover, comparative analyses of various optimization methods on the custom-built dataset reveal that the ant colony optimization algorithm markedly outperforms the simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO). …”
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Hyperspectral estimation of soil organic carbon content in the west lakeside oasis of Bosten Lake based on successive projection algorithm by NIU Fangpeng, LI Xinguo, MAMATTURSUN•Eziz, ZHAO Hui

“…Taking the west lakeside oasis of Bosten Lake as the study area, using the measured soil organic carbon content and hyperspectral data, the successive projection algorithm (SPA) was used to filter the characteristic variables from the full-band spectral data, and then the full-band and characteristic bands were used to construct partial least square regression (PLSR) and support vector machine (SVM) models to estimate soil organic carbon content. …”
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Estimation of Daylily Leaf Area Index by Synergy Multispectral and Radar Remote-Sensing Data Based on Machine-Learning Algorithm by Minhuan Hu, Jingshu Wang, Peng Yang, Ping Li, Peng He, Rutian Bi

“…The selected features were sensitive to daylily LAI. The RFR algorithm had good anti-noise performance and strong fitting ability; thus, its accuracy was better than the partial least squares regression and artificial neural network models. …”
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Development of an artificial intelligence-based algorithm to classify images acquired with an intraoral scanner of individual molar teeth into three categories. by Nozomi Eto, Junichi Yamazoe, Akiko Tsuji, Naohisa Wada, Noriaki Ikeda

“…In this study, we generated and evaluated an artificial intelligence-based algorithm that classified images of individual molar teeth into three categories: (1) full metallic crown (FMC); (2) partial metallic restoration (In); or (3) sound tooth, carious tooth or non-metallic restoration (CNMR).…”
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TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

“…Experimental results showed that: ① Compared with the Slime Mould Algorithm (SMA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Sparrow Search Algorithm (SSA), the ISMA optimization strategy demonstrated better convergence speed and optimization ability in multiple benchmark function tests. ② In the stress prediction experiment, ablation experiments verified the necessity of TCN, LSTM, and MHSA modules. ③ The ISMA-optimized TCN-LSTM-MHSA model outperformed mainstream prediction models such as BP and GRU in MAE, RMSE, and R2 metrics, showing higher prediction accuracy and stability.…”
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POMA-C: A Framework for Solving the Problem of Precise Anesthesia Control Under Incomplete Observation Environment in Low-Income Areas by Yide Yu, Huijie Li, Dennis Wong, Anmin Hu, Jian Huo, Yan Ma, Yue Liu

“…The framework employs the POMCPOW (Partially Observable Monte Carlo Planning with Observation Weighting) algorithm, which integrates Monte Carlo Tree Search (MCTS) and particle filtering to estimate the patient’s true physiological state and guide optimal anesthetic decisions. …”
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How to use learning curves to evaluate the sample size for malaria prediction models developed using machine learning algorithms by Sophie G. Zaloumis, Megha Rajasekhar, Julie A. Simpson

“…Learning curves were produced for two machine learning algorithms, sparse Partial Least Squares-Discriminant Analysis plus Support Vector Machines (sPLSDA + SVMs) and random forests. …”
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PO77 | The clinical awareness of mixing test interpretation in the era of complex reporting algorithm: do we forget the origins?

“… Background and Aims: Plasma mixing test is a simple laboratory procedure, which is performed on samples from patients with coagulation screening tests prolonged (mainly the activated partial thromboplastin (APTT), but also the prothrombin time (PT) or both). …”
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The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…SOM and PSD were then retrieved using combinations of ten spectral preprocessing methods (raw reflectance, Savitzky–Golay filter (SG), first derivative (D1), second derivative (D2), standard normal variate (SNV), multiplicative scatter correction (MSC), SG + D1, SG + D2, SG + SNV, and SG + MSC), one sensitive wavelength selection method, and three retrieval algorithms (partial least squares regression (PLSR), support vector machine (SVM), and convolutional neural networks (CNNs)). …”
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Optimization of Gear Modification Amount based on Polynomial Response Surface Proxy Model by Yonghua Li, Wusong Wei, Xu Zhang

“…The optimal modification amount obtained by the particle swarm algorithm is used for gear modification， the maximum contact stress of the gear meshing process is reduced， the transmission error is reduced， and the eccentric load phenomenon is effectively improved.…”
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Simulations of the sterile neutrino oscillations with a crossing-width term by Qiankang Wang, DaYun Qiu, Yi-Lei Tang

“…We prove the validity of our algorithm, and adopt some tricks for practical calculations. …”
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Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance by Mahmoud M. Eid, Kamal ElDahshan, Abdelatif H. Abouali, Alaa Tharwat

“…The first set uses synthetic datasets to compare four optimization algorithms—Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and the Sine–Cosine Algorithm (SCA)—to determine which one best identifies features related to the target feature. …”
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Clutaxis: An information-driven source search method balancing exploration and exploitation in turbulent environments by Runkang Guo, Yong Zhao, Yatai Ji, Mengyu Yan, Zhengqiu Zhu

“…To address these issues, this paper proposes a novel information-driven search method called Clutaxis, based on a global exploration and exploitation tradeoff principle. Specifically, a particle filter is leveraged to maintain the STE. After projecting the particle filter samples onto a 2D search scene, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to extract the density information of the samples, which is then used to construct a belief source area (BSA). …”
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A Method of Smoke Area Segmentation for Infrared Images Based on Deep Learning by QI Hang, YUAN Jianquan, LI Lei, REN Jun, LIANG Jie

“…Then, the Deeplab v3+ algorithm was used for smoke segmentation. When testing on the real image data set, a satisfactory segmentation result with 79 percent has been reached which can meet the usage requirements, illustrating that our method is effective and efficient.…”
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Transformer–BiLSTM Fusion Neural Network for Short-Term PV Output Prediction Based on NRBO Algorithm and VMD by Xiaowei Fan, Ruimiao Wang, Yi Yang, Jingang Wang

“…Then, the Transformer decoder partially fuses the BiLSTM network and retains the encoder to obtain the body of the prediction model, followed by explaining the principle of the NRBO algorithm. …”
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