Fractional Optimizers for LSTM Networks in Financial Time Series Forecasting by Mustapha Ez-zaiym, Yassine Senhaji, Meriem Rachid, Karim El Moutaouakil, Vasile Palade

“…These results suggest that fractional-order optimization holds significant promise for improving financial forecasting models—provided that the fractional parameters are carefully tuned to balance memory effects with system stability.…”
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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. The test results of KITTI and CCTSDB2021 public traffic datasets show that compared with the original YOLOv5 model, the improved algorithm reduces the number of parameters by 20%, the calculation amount by 21%, and mAP@0.5 by 1.0%. …”
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An integrated AHP-GP-GA approach for public project portfolio selection problem by A.O. Mogbojuri, O.A. Olanrewaju

“…The selection of projects via an effective methodology is rare, as numerous approaches are considered useless due to constraints on the number of projects available and the inability to identify cost-efficient initiatives. The study presents integrated models of the Analytic Hierarchy Process, Goal Programming, and Genetic Algorithm (AHP-GP-GA) by removing the bias of each model for Public PPSP and building a relationship between the developed models.The AHP method was utilized to establish project selection criteria, allocate relative priority values to stakeholders, and calculate the overall weighting of project alternatives. …”
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RESEARCH ON PERFORMANCE PREDICTION OF THIN SEAM SHEARER BY COMBINING GENETIC ALGORITHM WITH BP NEURAL NETWORK by ZHAO LiJuan, JIN ZhongFeng

“…Established mathematical model of thin seam shearer,we use genetic algorithm to optimize the weighted values and threshold values of the BP neural network,using the simulation data for training and testing samples,and then use the BP algorithm to train the neural network,thus avoiding the local minimum values when the training is done with the BP neural network alone. …”
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Quality of Experience Optimization for AR Service in an MEC Federation System by Huong Mai do, Tuan Phong Tran, Myungsik Yoo

“…To address this shortcoming, we studied AR subtask offloading and resource allocation in a multi-hop, multi-access edge computing federation. Our approach improves the quality of experience (QoE) by optimizing video quality and reducing delay while ensuring fairness, which is modeled as the ratio between provided and required quality. …”
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FONDUE—Fine-Tuned Optimization: Nurturing Data Usability & Efficiency by Valerie Restat, Indra Diestelkämper, Meike Klettke, Uta Störl

“…As an adaptive and easily extendable framework, FONDUE operates similarly to proven methods of database query optimization. Analogously, it consists of the following parts: Rule-based optimization, where the appropriate data cleaning algorithms are selected based on use case constraints, optimizer hints in the form of best practices, and cost-based optimization, where the costs are measured in terms of data quality. …”
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A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach by Srikanth Meda, Vangipuram Sesha Srinivas, Killi Chandra Bhushana Rao, Repudi Ramesh, Narasimha Rao Yamarthi

“…The final phase involves classifying the data using the Shallow hybrid quantum-classical convolutional neural network (SHQCNN) model. To improve the effectiveness of the classification approach, the hyperparameters present in the SHQCNN model are fine-tuned using the shuffled shepherd optimization algorithm (SSOA). …”
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Application of quasi-oppositional driving training-based optimization for a feasible optimal power flow solution of renewable power systems with a unified power flow controller by Tushnik Sarkar, Chandan Paul, Susanta Dutta, Provas Kumar Roy, Ghanshyam G. Tejani, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…The acquired test outcomes by QODTBO have been contrasted with the outcomes found by the use of DTBO, backtracking search optimization algorithm (BSA), and sine cosine algorithm (SCA). …”
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Optimal entanglement distribution within a multi-ring topology by B. C. Ciobanu, T. A. Calafeteanu, A. B. Popa, R. Tătăroiu, P. G. Popescu

“…We propose algorithms that solve the problem of entanglement distribution in terms of optimal time needed to satisfy a set of entanglement resupply requests with given network resources, as well as the problem of optimal resources in order to satisfy a set of entanglement resupply requests within a single entanglement transmission and measurement step. …”
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Quantifying and optimizing single-molecule switching nanoscopy at high speeds. by Yu Lin, Jane J Long, Fang Huang, Whitney C Duim, Stefanie Kirschbaum, Yongdeng Zhang, Lena K Schroeder, Aleksander A Rebane, Mary Grace M Velasco, Alejandro Virrueta, Daniel W Moonan, Junyi Jiao, Sandy Y Hernandez, Yongli Zhang, Joerg Bewersdorf

“…Recent advances in this technique have greatly accelerated the data acquisition speed and improved the temporal resolution of super-resolution imaging. …”
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Efficiency Optimization of PMSM-Type Elevator Machine: An Industrial Comparison by Mucahit Soyaslan, Osman Eldogan, Ahmet Fenercioglu, Yusuf Avsar, Nurdogan Ceylan, Muhammed Salih Sarıkaya

“…Critical parameters, including stator tooth tip thickness, slot tip radius, slot height, stator yoke height, stator tooth thickness, and the number of turns per phase, were optimized to enhance efficiency. The artificial bee colony (ABC) algorithm was utilized for the first time to determine the optimal configuration of an external rotor PMSM. …”
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Analysis of the thermal distribution of a porous radial fin influenced by an inclined magnetic field with neural computing by Shazia Habib, Waseem, Zeeshan Khan, Salah Boulaaras, Mati ur Rahman, Saeed Islam, Rafik Guefaifia

“…This innovative approach offers a sophisticated solution for complex thermal models, improved prediction accuracy for nonlinear heat transfer, parameter-driven optimization in porous media heat transfer, and increased model efficiency for real-time thermal management.…”
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Heating Load Prediction with Meta-Heuristic ‎Algorithms and Adaptive Neuro-Fuzzy ‎Inference System Integration by Seyed Hadi Seyed Hatami, Reza Seifi Majdar

“…To enhance predic-tive accuracy, two meta-heuristic algorithms, the Reptile Search Algorithm (RSA) and the Flow Direction Algorithm (FDA), are seamlessly integrated into the Adaptive Neuro-Fuzzy Inference System (ANFIS) model. …”
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A Distributed Parallel Genetic Algorithm of Placement Strategy for Virtual Machines Deployment on Cloud Platform by Yu-Shuang Dong, Gao-Chao Xu, Xiao-Dong Fu

“…The solution calculated by the genetic algorithm of the second stage is the optimal one of the proposed approach. …”
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The Evolution of Portfolio Theory: Integrating Machine Learning with Markowitz Optimization by Xu Junhao

“…An empirical analysis utilizing recent U.S. market data reveals that ML models improve risk assessment, asset selection, and adaptive portfolio allocation. …”
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A Fast and Efficient Beamforming Algorithm Imitating Plant Growth Gene for Phased Array Antenna by Jinling Zhang, Chen Han, Zhanqi Zheng, Xiongzhi Zhu, Xiaohui Li

“…This algorithm converts the complex optimization process of array antenna excitation by the classical optimization algorithm into a simple process of fine-tuning the gain at any angle on the beam to make it grow and approach the target pattern. …”
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IMPROVE OF UNCERTAIN MICROSATELLITE MAGNETIC CLEANLINESS BASED ON MAGNETIC FIELD SPATIAL HARMONICS COMPENSATION by Б.І. Кузнецов, Т.Б. Нікітіна, І.В. Бовдуй, К.В. Чуніхін, В.В. Коломієць, Б.Б. Кобилянський

“…Both vector game solution calculated based on particles multi-swarm optimization (PMSO) algorithms from Pareto optimal solutions taking into account binary preference relations. …”
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Enhanced NDVI prediction accuracy in complex geographic regions by integrating machine learning and climate data—a case study of Southwest basin by Zehui Zhou, Jiaxin Jin, Bin Yong, Weidong Huang, Lei Yu, Peiqi Yang, Dianchen Sun

“…To address these limitations, this study developed an NDVI time-series prediction optimization model, LSKRX, which integrates multiple machine learning algorithms with local geographic and climatic data. …”
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Improved Quantum Query Upper Bounds Based on Classical Decision Trees by Arjan Cornelissen, Nikhil S. Mande, Subhasree Patro

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A cooperative stochastic configuration network based on differential evolutionary sparrow search algorithm for prediction by Wenhao Fang, Bo Shen, Anqi Pan, Lei Zou, Baoye Song

“…To improve the prediction accuracy of the network, a cooperative stochastic configuration network (CSCN) based on a novel differential evolutionary sparrow search algorithm (DESSA), termed as DESSA-CSCN, is proposed. …”
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