Hybrid deep learning optimization for smart agriculture: Dipper throated optimization and polar rose search applied to water quality prediction. by Amal H Alharbi, Faris H Rizk, Khaled Sh Gaber, Marwa M Eid, El-Sayed M El-Kenawy, Ehsan Khodadadi, Nima Khodadadi

“…Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dipper Throated Optimization (DTO), a bio-inspired algorithm modeled on bird foraging behavior, with Polar Rose Search (PRS) to enhance deep learning models in predictive water quality assessment. …”
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Enhancing the Efficiency of Routing Strategies in WSNs Using Live Streaming Algorithms by Hayder Jasim Alhamdane, Mohsen Nickray

“…The goal of conventional green routing algorithms is to reduce energy consumption and increase network life cycles by improving routing schemes in wireless networks. …”
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A Quantum-like Approach to Semantic Text Classification by Anastasia S. Gruzdeva, Rodion N. Iurev, Igor A. Bessmertny, Andrei Y. Khrennikov, Alexander P. Alodjants

“…We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. …”
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Application of Genetic Algorithms to Solve MTSP Problems with Priority (Case Study at the Jakarta Street Lighting Service) by Sugih Sudharma Tjandra, Fran Setiawan, Hanoum Salsabila

“…In its development based on actual events in the real world, some priorities must be visited first in optimizing vehicle routes. Several studies on MTSP and CVRP models have been conducted with exact solutions and algorithms. …”
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Design of Enhanced License Plate Information Recognition Algorithm Based on Environment Perception by Zilu Wang, Limin Zheng, Gang Li

“…Comparing the H-YOLO detector with the baseline YOLOv11 model, we found that the training precision and recall of our model were improved by 2.62% and 1.8%, respectively. …”
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A New LQR Optimal Control for a Single-Link Flexible Joint Robot Manipulator Based on Grey Wolf Optimizer by Navid Razmjooy, Mehdi Ramezani, Ali Namadchian

“…By considering the proposed performance index and comparing with the PSO-based controller as a popular algorithm, the superiority of the proposed LQR controller in improving the stability and performance of the manipulator is shown. …”
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A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network by Kui Liu, Sanyang Liu, Hailin Feng

“…A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. …”
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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

“…Gradient boosting machine (GBM) models were optimized using advanced algorithms like self-adaptive differential evolution (SADE), evolution strategy (ES), Bayesian probability improvement (BPI), and Batch Bayesian optimization (BBO). …”
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An Enhanced Interval Type-2 Fuzzy C-Means Algorithm for Fuzzy Time Series Forecasting of Vegetation Dynamics: A Case Study from the Aksu Region, Xinjiang, China by Yongqi Chen, Li Liu, Jinhua Cao, Kexin Wang, Shengyang Li, Yue Yin

“…Fuzzy time series (FTS) prediction models based on the Fuzzy C-Means (FCM) clustering algorithm address some of these uncertainties by enabling soft partitioning through membership functions. …”
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Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…We examine various metaheuristic algorithms employed and, in particular, their effectiveness in improving model performance across diverse applications. …”
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Flexible scheduling strategy for power systems considering source-load uncertainty by Qunmin YAN, Xiaoyu REN, Xiao SONG, Mengjue ZHAO, Chen AN

“…The two-stage robust model is transformed into relatively independent main problems and sub-problems，and the column constraint generation （C&CG） algorithm and strong dyadic theory are adopted to iterate repeatedly to approximate the optimal solution. …”
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Energy and channel transmission management algorithm for resource harvesting body area networks by Zhigang Chen, Lin Guo, Deyu Zhang, Xuehan Chen

“…Based on the proposed model, we formulate an optimization problem of system utility maximization. …”
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Modelo matemático y algoritmo de solución de un flujo con tiempos dependientes de la secuencia // A mathematical model and solution algorithm to a flow shop task with times dependi... by A. Fiol-Zulueta, J. Arzola-Ruíz, A. da Silva-Carvalho

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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…It is required to enhance data processing, improve model generalization by preprocessing and synthesizing data, and optimize model adaptability in changing environments. …”
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A Ｒeinforcement Learning of Cloud Ｒesource Scheduling Algorithm Based on Adaptive Weight by LI Cheng-yan, SUN Wei, TANG Li-min

“…We considered the cloud computing resource scheduling problem，and proposed a multi-objective optimization mathematical model to optimize task completion time and running cost simultaneously. …”
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Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation by Nasreddine Bouchikhi, Fethi Boussadia, Riyadh Bouddou, Ayodeji Olalekan Salau, Saad Mekhilef, Chaima Gouder, Sarra Adiche, Abdallah Belabbes

“…The MGWO algorithm is an improved version of the conventional GWO algorithm, which is based on a hierarchical model inspired by the social behavior of grey wolves. …”
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Bio inspired feature selection and graph learning for sepsis risk stratification by D. Siri, Raviteja Kocherla, Sudharshan Tumkunta, Pamula Udayaraju, Krishna Chaitanya Gogineni, Gowtham Mamidisetti, Nanditha Boddu

“…To further improve predictive accuracy, the TOTO metaheuristic algorithm is applied for model fine-tuning. …”
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Progressive filling partitioning and mapping algorithm for Spark based on allocation fitness degree by Chen BIAN, Jiong1 YU, Wei-rong XIU, Bin LIAO, Chang-tian YING, Yu-rong QIAN

“…The job execution mechanism of Spark was analyzed,task efficiency model and Shuffle model were established,then allocation fitness degree (AFD) was defined and the optimization goal was put forward.On the basis of the model definition,the progressive filling partitioning and mapping algorithm (PFPM) was proposed.PFPM established the data distribution scheme adapting Reducers’ computing ability to decrease synchronous latency during Shuffle process and increase cluster the computing efficiency.The experiments demonstrate that PFPM could improve the rationality of workload distribution in Shuffle and optimize the execution efficiency of Spark.…”
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Combined use of near infrared spectroscopy and chemometrics for the simultaneous detection of multiple illicit additions in wheat flour by Xinyi Dong, Ying Dong, Jinming Liu, Siting Wu

“…Compared to regression models built with competitive adaptive reweighted sampling and genetic algorithm for feature wavelength selection, the performance improved significantly, enhancing generalization capability. …”
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Deep learning-based feature selection for detection of autism spectrum disorder by Ibrahim Nafisah, Nermine Mahmoud, Ahmed A. Ewees, Mohamed G. Khattap, Abdelghani Dahou, Safar M. Alghamdi, Ibrahim A. Fares, Mohammed Azmi Al-Betar, Mohammed Azmi Al-Betar, Mohamed Abd Elaziz, Mohamed Abd Elaziz

“…Feature selection is enhanced through an optimized Hiking Optimization Algorithm (HOA) that integrates DynamicOpposites Learning (DOL) and Double Attractors to improve convergence toward the optimal subset of features.ResultsThe proposed model is evaluated using multiple ASD datasets. …”
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