Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…Convolutional Neural Networks are used to extract spatial features from agricultural data, while Long Short-Term Memory networks processed time series data. …”
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FECI-RTDETR a Lightweight Unmanned Aerial Vehicle Infrared Small Target Detector Algorithm Based on RT-DETR by Renzheng Xue, Shijie Hua, Haiqiang Xu

“…This paper proposes a lightweight UAV infrared small target detection algorithm, FECI-RTDETR. Initially, we introduce a lightweight RFConv-Block module that enhances spatial feature extraction capabilities while reducing computational redundancy. …”
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Evaluating machine leaning algorithms for accuracy, stability, and among-predictors discriminability in modeling species-richness across ten datasets by Yong Cao, Tyler E. Schartel, David C. Houghton, Jared Ross, Dana M. Infante

“…Global biodiversity is experiencing substantial declines, and mitigating this crisis requires analytical approaches that can accurately predict biodiversity in relation to natural conditions and human-induced stressors. While numerous machine learning (ML) algorithms for regression are available for such analyses, synthesizing outcomes across studies is challenging due to: (1) reliance on single datasets, limiting generalizability; (2) varying modeling processes; (3) inconsistent performance criteria; and (4) limited consideration of model stability and among-predictor discriminability.We addressed these issues by applying five ML algorithms—Random Forest (RF), Boosted Regression Tree (BRT), Extreme Gradient Boosting (XGB), Conditional Inference Forest (CIF), and Lasso—to ten large datasets on freshwater fish, mussels, and caddisflies. …”
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Collaborative Optimization on Both Weight and Fatigue Life of Fifth Wheel Based on Hybrid Random Forest with Improved BP Algorithm by Huan Xue, Chang Guo, Xiaojian Peng, Saiqing Xu, Kaixian Li, Jianwen Li

“…We proposed a prediction model combining a random forest algorithm with an optimized back propagation (BP) neural network. …”
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Collaborative Search Algorithm for Multi-UAVs Under Interference Conditions: A Multi-Agent Deep Reinforcement Learning Approach by Wei Wang, Yong Chen, Yu Zhang, Yong Chen, Yihang Du

“…The framework exhibits strong resilience to communication disruptions while maintaining stable search performance, validating its practical applicability in real-world interference scenarios.…”
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Decoding basic emotional states through integration of an fNIRS-based brain-computer interface with supervised learning algorithms. by Ayşenur Eser, Sinem Burcu Erdoğan

“…Three class classification performances of all algorithms were above 90% in terms of accuracy, sensitivity, specificity, F-1 score and precision metrics while two class accuracy performances of all algorithms were above 93% in terms of each performance metric. …”
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NETWORK MODEL AND ALGORITHM FOR SOLVING PROBLEM OF OPTIMUM THERMAL LOAD DISTRIBUTION AMONG HEAT-SOURCES OF ENTERPRISE HEATING SYSTEM by V. A. Sednin, A. D. Korznikov, А. V. Sednin, I. V. Masevich

“…The algorithm can be used while elaborating plans for development of heat supply systems in cities and settlements.…”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…Optimizing soil nutrient prediction models is important for achieving maximum agricultural output and sustainability while also ensuring effective resource management and environmental protection, as demonstrated by a case study in Johannesburg, South Africa. …”
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Integrated neural network and evolutionary algorithm approach for liver fibrosis staging: Can artificial intelligence reduce patient costs? by Ali Nazarizadeh, Touraj Banirostam, Taraneh Biglari, Mohammadreza Kalantarhormozi, Fatemeh Chichagi, Amir H Behnoush, Mohammad A Habibi, Ramin Shahidi

“…The accuracy of MLP using 12 features is 0.903, while that of the proposed MLP with TLBO is 0.891. …”
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Finite Element Model Updating for a Continuous Beam-Arch Composite Bridge Based on the RSM and a Nutcracker Optimization Algorithm by Weihua Zhou, Hongyin Yang, Jing Hao, Mengxiang Zhai, Hongyou Cao, Zhangjun Liu, Kang Wang

“…The results indicate that the proposed method reduced the average frequency error from 5.58% to 2.75% by updating the model parameters. While the whale optimization algorithm required 21 iterations and the grey wolf optimizer needed 41 iterations to converge near the minimum, the NOA achieved this in merely 13 iterations, demonstrating the NOA’s superior convergence speed. …”
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Acoustic response discrimination of phulae pineapple maturity and defects using factor analysis of mixed data and machine learning algorithms by Sujitra Arwatchananukul, Saowapa Chaiwong, Nattapol Aunsri, Sila Kittiwachana, Kietsuda Luengwilai, Tatiya Trongsatitkul, Pramod Mahajan, Jose Blasco, Rattapon Saengrayap

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Global optimization of economic load dispatch in large scale power systems using an enhanced social network search algorithm by Mohamed H. Hassan, Salah Kamel, Francisco Jurado, Umberto Desideri

“…The primary goal is to improve the algorithm's ability to explore global search possibilities while avoiding being trapped in locally optimal solutions. …”
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Multi-objective optimization framework for electric vehicle charging and discharging scheduling in distribution networks using the red deer algorithm by Sahbi Boubaker, Habib Kraiem, Nejib Ghazouani, Souad Kamel, Adel Mellit, Faisal S. Alsubaei, Farid Bourennani, Walid Meskine, Tariq Alqubaysi

“…To tackle the optimization problem, a metaheuristic swarm intelligence algorithm, the Red Deer Algorithm (RDA), is utilized to determine the optimal EV charging and discharging timings. …”
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Investigate on dynamic mechanical and mesoscopic damage characteristics of high-temperature treated granite based on SPH-FEM coupling algorithm by Liu Zilu, Yu Weijian, Wu Genshui, Zhang Zizheng, Wang Ping

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URT-YOLOv11: A Large Receptive Field Algorithm for Detecting Tomato Ripening Under Different Field Conditions by Di Mu, Yuping Guou, Wei Wang, Ran Peng, Chunjie Guo, Francesco Marinello, Yingjie Xie, Qiang Huang

“…This study proposes an improved YOLOv11 model to address the limitations of traditional tomato recognition algorithms in complex agricultural environments, such as lighting changes, occlusion, scale variations, and complex backgrounds. …”
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Target tracking algorithm for wireless sensor networks based on particle swarm optimization and metropolis-hasting sampling particle filter by Peng JIANG, Hua-hua SONG, Guang LIN

“…For the characteristic of the nonlinear relationship between the observation information of sensor nodes and the target dynamic parameters under the real application conditions, a target tracking algorithm for wireless sensor networks based on particle swarm optimization and Metropolis-Hasting sampling particle filter was proposed. …”
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Improving Systematic Review Updates With Natural Language Processing Through Abstract Component Classification and Selection: Algorithm Development and Validation by Tatsuki Hasegawa, Hayato Kizaki, Keisho Ikegami, Shungo Imai, Yuki Yanagisawa, Shuntaro Yada, Eiji Aramaki, Satoko Hori

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AI-driven optimization of indoor environmental quality and energy consumption in smart buildings: a bio-inspired algorithmic approach by Rehab Salaheldin Ghoneim, Mazin Arabasy, Ashraf Nadheer Abdulhadi

“…This work presents an in-depth analysis of five bio-inspired optimization algorithms, namely Puma Optimizer (PO), Walrus Optimizer (WO), Flying Fox Optimization Algorithm (FFO), Waterwheel Plant Algorithm (WWPA), and Energy Valley Optimizer (EVO), which optimize the energy consumption while keeping the occupants’ comfort intact within smart building environments. …”
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A novel quality of service-aware task scheduling approach for cloud computing using modified Wombat Optimization Algorithm by Lijuan Yan

“…In the Internet of Things (IoT) applications, there is a significant need to identify efficient methods for allocating computational resources or reducing cost and latency while maintaining the reliability of services. Most existing scheduling algorithms encounter difficulties in terms of premature convergence and suboptimal performance in multi-objective scenarios. …”
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LMAD-YOLO: A vehicle image detection algorithm for drone aerial photography based on multi-scale feature fusion. by Xue Xing, Fahui Luo, Le Wan, Kang Lu, Yuqi Peng, Xiujuan Tian

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