A carbon aware ant colony system for the sustainable generalized traveling salesman problem by Marina Lin, Laura P. Schaposnik

“…Our algorithm’s unique bi-objective optimization represents a significant advancement in sustainable transportation solutions strategically balancing cost and carbon emissions to reduce energy consumption and promote environmental responsibility.…”
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Bayesian-optimized ensemble deep learning models for demand forecasting in the volatile situations: A case study of grocery demand during Covid-19 outbreaks by Nader AL Theeb, Hazem Smadi, Naser Al-qaydeh

“…Furthermore, using BO algorithm for hyperparameters tuning improved the forecasting accuracy. …”
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Construction of an oligometastatic prediction model for nasopharyngeal carcinoma patients based on pathomics features and dynamic multi-swarm particle swarm optimization support ve... by Yunfei Li, Dongni Zhang, Yiren Wang, Yiren Wang, Yiheng Hu, Zhongjian Wen, Zhongjian Wen, Cheng Yang, Ping Zhou, Wen-Hui Cheng

“…ObjectiveThis study aimed to develop a risk prediction model for post-treatment oligometastasis in nasopharyngeal carcinoma (NPC) by integrating pathomics features and an improved Support vector machine (SVM) algorithm, offering precise early decision support.MethodsThis study retrospectively included 462 NPC patients, without or with oligometastasis defined by ESTRO/EORTC criteria. …”
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Yield Diagnosis and Tuning for Emerging Semiconductors During Research Stage by Chunshan Wang, Zizhao Ma, Yuxuan Zhu, Chensheng Jin, Dongyu Chen, Chuxin Zhang, Yining Chen, Wenzhong Bao, Yufeng Xie

“…The process of taking a new semiconductor device from the lab to the factory involves a lot of time, funds and manpower, a large portion of which is spent on device yield improvement. In recent years new methods have been tried to rapidly improve yields and using machine learning (ML) algorithms is one option. …”
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Leveraging RRT^*: Probabilistically Interpreted Mechanisms Enhanced With P-HOPE and FLEX-OPT for Complex Path Planning by Yujie Miao, Haiyang Liu, Ziqiang Zhang, Yanju Liang

“…Second, a flexible mechanism FLEX-OPT is developed to adaptively and dynamically adjust the search strategy through real-time feedback and monitoring of the cost function to tackle the above-mentioned local minima problem, which significantly improves the convergence speed and path quality of the algorithm. …”
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An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system by Bishwajit Dey, Gulshan Sharma, Pitshou N. Bokoro, Soham Dutta

“…Abstract The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. …”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…In conducting multi-objective optimization for both the airfoil and serration shapes, the study demonstrates notable improvements: a 5 to 7% enhancement in aerodynamic performance alongside a simultaneous 1-4% reduction in noise compared to benchmark airfoils. …”
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Empowering Fuel Cell Electric Vehicles Towards Sustainable Transportation: An Analytical Assessment, Emerging Energy Management, Key Issues, and Future Research Opportunities by Tuhibur Rahman, Md. Sazal Miah, Tahia F. Karim, Molla Shahadat Hossain Lipu, Abu M. Fuad, Zia Ul Islam, M. M. Naushad Ali, Mohammed Nazmus Shakib, Shafrida Sahrani, Mahidur R. Sarker

“…To address these challenges, smart energy management involving appropriate converters, controllers, intelligent algorithms, and optimizations is essential for enhancing the effectiveness of FCEVs towards sustainable transportation. …”
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An enhanced approach for automatic annotation of error codes based on Seq2edit by Jian Wang, Tao Lin, Rongsen Zhao, Huiling Zhao

“…By dividing the code into statements with independent meanings and introducing a cost coefficient to improve the Levenshtein algorithm, this method optimizes the calculation of edit distance and enhances the ability to align tokens. …”
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Optimal Power Flow for High Spatial and Temporal Resolution Power Systems with High Renewable Energy Penetration Using Multi-Agent Deep Reinforcement Learning by Liangcai Zhou, Long Huo, Linlin Liu, Hao Xu, Rui Chen, Xin Chen

“…A heterogeneous multi-agent proximal policy optimization (H-MAPPO) DRL algorithm is introduced for multi-area power systems. …”
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Prototype Mobile Vision System for Automatic Length Estimation of Olive Flounder (<i>Paralichthys olivaceus</i>) in Indoor Aquaculture by Inyeong Kwon, Hang Thi Phuong Nguyen, Paththige Waruni Prasadini Fernando, Hieyong Jeong, Sungju Jung, Taeho Kim

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Comparative analysis of lumped and semi-distributed hydrological models for an upland watershed in Ethiopia by Gebiaw T. Ayele, Bofu Yu

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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Accurate prediction of electricity price (EP) is crucial for energy utilities and grid operators for enhancing the energy trading, grid stability studies, resource allocations and pricing strategies, thereby improving the overall grid reliability, efficiency, and cost-effectiveness. …”
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A Miniaturized and Intelligent Lensless Holographic Imaging System With Auto-Focusing and Deep Learning-Based Object Detection for Label-Free Cell Classification by Jin Chen, Wentao Han, Liangzun Fu, Zhihang Lv, Haotian Chen, Wenjing Fang, Jiale Hou, Haohan Yu, Xiwei Huang, Lingling Sun

“…Our system uses unstained cells suspended in solution as samples and employs a threshold segmentation-based auto-focusing algorithm to determine the optimal focusing distance for each imaging session. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…Different cost functions have been tested and evaluated to improve the diagnostic performance. …”
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Torsional Vibration Characterization of Hybrid Power Systems via Disturbance Observer and Partitioned Learning by Tao Zheng, Hui Xie, Boqiang Liang

“…In contrast, incorporating the parameter self-learning algorithm reduces the RMSE to 2.36 N·m, representing an 85.2% improvement in estimation accuracy. …”
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Prediction of lithium-ion battery SOC based on IGA-GRU and the fusion of multi-head attention mechanism by Pei Tang, Minnan Jiang, Weikai Xu, Zhengyu Ding, Mao Lv

“…Compared with the traditional parameter optimization approach, this paper uses the immune genetic algorithm to find the optimal hyperparameters of the model, which on the one hand has a wider choice of parameters, and on the other hand has been improved for the genetic algorithm is easy to fall into the local optimal solution, so as to improve the SOC estimation accuracy of the GRU model. …”
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SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks by Sneh Pandya, Purvik Patel, Brian D Nord, Mike Walmsley, Aleksandra Ćiprijanović

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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…Moreover, understanding the relative importance and contribution of different waste properties to HHV prediction is critical for improving the model's predictive capability and optimizing the waste-to-energy (WTE) process. …”
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A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

“…To address this, effective feature selection is essential but remains an NP-hard challenge best tackled with heuristic algorithms. This study introduces a binary, multi-objective starfish optimizer for optimal feature selection, balancing feature reduction and classification performance. …”
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