Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience by Tzu-Chien Wang, Ruey-Shan Guo, Chialin Chen, Chia-Kai Li

“…To address these limitations, this study proposes a multi-stage data-driven framework integrating latent Dirichlet allocation (LDA) for behavioral insights, deep learning for predictive modeling, and heuristic algorithms for adaptive decision-making. …”
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Mental Workload Detection and Assessment Through Statistical Features Extraction and Optimization Using GEL-RF Method for EEG Signals Using N-Back Dataset by Waleed Manzoor, Noman Naseer, Imran Fareed Nizami, Syed Hammad Nazeer, Husam A. Neamah

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Research on the Capability Maturity Evaluation of Intelligent Manufacturing Based on Firefly Algorithm, Sparrow Search Algorithm, and BP Neural Network by Li Shi, Xuehong Ding, Min Li, Yuan Liu

“…In order to overcome the shortcoming of SSA that it is easy to fall into the local optimum, the firefly disturbance strategy is introduced to improve it, a new sparrow search algorithm (FASSA) is proposed, and on this basis, an intelligent manufacturing capability maturity evaluation model based on the FASSA-BP algorithm is constructed. …”
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Developing and Implementing an Artificial Intelligence (AI)-Driven System For Electricity Theft Detection by Nwamaka Georgenia Ezeji, Kingsley Ifeanyi Chibueze, Nnenna Harmony Nwobodo-Nzeribe

“…Methodology used are data collection, data analysis, feature selection with Chi-Square, feature transformation with Principal Component Analysis (PCA), Support Vector Machine (SVM) and model for electricity theft detection.   To achieve this, a Particle Swarm Optimization Algorithm (PSO) was applied to improve training performance of the SVM, using data of meter recharge information collected from Enugu Electricity Distribution Company (EEDC). …”
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Multi-dimensional constraint-based coal mining machine cutting path planning technology by Shuyang SONG, Shibo WANG, Yun WANG, Lijie WANG, Dongshuai SONG

“…NSGA-II algorithm is used to solve for the optimal cutting path. …”
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Advanced Cotton Boll Segmentation, Detection, and Counting Using Multi-Level Thresholding Optimized with an Anchor-Free Compact Central Attention Network Model by Arathi Bairi, Uma N. Dulhare

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A cellular automata coupled multi-objective optimization framework for blue-green infrastructure spatial allocation by Qinghe Hou, Hanwen Xu, Mingkun Xie, Pingjia Luo, Yuning Cheng

“…In this study, a multi-objective optimization framework was developed to address these challenges by integrating a Cellular Automata (CA)-based hydrological model with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). …”
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Atomic Energy Optimization: A Novel Meta-Heuristic Inspired by Energy Dynamics and Dissipation by Mohammed Omari, Mohammed Kaddi, Khouloud Salameh, Ali Alnoman, Mohammed Benhadji

“…AEO models optimization by mimicking the energy accumulation, transfer, and dissipation behaviors observed in atoms, particularly during processes involving electrostatic charge and discharge. …”
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Study on Tourism Development Using CRITIC Method for Tourist Satisfaction by Xi Yang, Noor Azman Ali, Huam Hon Tat

“…This paper presents a novel approach for evaluating tourist satisfaction and developing optimized strategies by integrating the CRITIC method, deep learning with Multilayer Perceptron (MLP), and Genetic Algorithms (GA). …”
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Spatial Downscaling of TRMM Precipitation Data Using an Optimal Subset Regression Model with NDVI and Terrain Factors in the Yarlung Zangbo River Basin, China by Jinping Liu, Wanchang Zhang, Ning Nie

“…The objective of this study was to develop a reliable statistical downscaling algorithm to produce high quality, high spatial resolution precipitation products from Tropical Rainfall Monitoring Mission (TRMM) 3B43 data over the Yarlung Zangbo River Basin using an optimal subset regression (OSR) model combined with multiple topographical factors, the Normalized Difference Vegetation Index (NDVI), and observational data from rain gauge stations. …”
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AI driven automation for enhancing sustainability efforts in CDP report analysis by Ramya Rangarajan, Tamilarasi Kathirvel Murugan, Logeswari Govindaraj, Venyaa Venkataraman, Krithik Shankar

“…The hybrid model consists of two main components: LSTM networks for predictive modeling of emission trends and GA for optimization of supply chain processes. …”
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Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling by He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Chen Chen, Junyu Wu, Yanjie Song

“…This increased demand for complex and diverse imaging products requires addressing multi-objective optimization in practice. To this end, we propose a multi-objective agile Earth observation satellite scheduling problem (MOAEOSSP) model and introduce a reinforcement learning-based multi-objective grey wolf optimization (RLMOGWO) algorithm. …”
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Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model by Chuansheng Zhang, Minglai Yang

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Deep learning framework based on ITOC optimization for coal spontaneous combustion temperature prediction: a coupled CNN-BiGRU-CBAM model by Xuming Shao, Wenhao Liu, Gang Bai, Yan Chen, Yu Liu, Jiahe Guang

“…Based on these variables, a deep learning framework combining an Improved Tornado Optimization with Coriolis force (ITOC) strategy and a CNN-BiGRU-CBAM model is proposed. …”
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A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…The P-BTLBO method combines probabilistic modeling with a bi-level optimization framework to make feature selection better. …”
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Optimizing EV charging stations and power trading with deep learning and path optimization. by Qing Zhu

“…Path optimization, using the Dijkstra algorithm, minimized travel times for EV users by 11.4%. …”
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Improving the efficiency of adsorption filters with a short diffuser by improving their flow part by A. S. Korneeva, N. Yu. Filkin

“…The numerical studies cover various options for backfilling the adsorbent, including layer profiling and the use of adsorbent with different porosity, which allows us to assess the impact of these factors on the aerodynamic resistance and overall efficiency of the filter. A design algorithm is also proposed that ensures optimal compliance between the adsorbent layer thickness and the local flow velocity, which helps to increase the protective action time of the filter and improve the quality of cleaning.…”
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An Adaptive Task Traffic Shaping Method for Highly Concurrent Geographic Information System Services with Limited Resources by Zheng Wu, Hongyun Zhou, Zezhao Wang, Pengda Wu, Zhaoting Ma

“…The relationship between the task arrival rate and server load is established based on the queueing theory model, and the token fill rate of the token bucket is adjusted adaptively according to resource load evaluation, so as to optimize the task processing flow. …”
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Enhanced recurrent attention-deep Q learning with optimal node constrains and effective penalty based model for data transmission scheduling on wireless sensor networks by D.R. Anita Sofia Liz, Yesubai Rubavathi C

“…This technique performs dynamic scheduling of data transmission tasks considering energy consumption and network interference by combining a penalty-based model, optimal node limitations, and recurrent attention techniques. …”
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Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments by Amin Wen, Tonghua Wu, Xiaofan Zhu, Jie Chen, Jianzong Shi, Peiqing Lou, Dong Wang, Xin Ma, Xiaodong Wu

“…The results show that (i) the lowest <i>t</i> value (0°) captured the microtopograhy of the troughs, while the larger <i>L</i> values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. …”
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