Identification and Evaluation of Profitable Technical Trading Rules in the Cryptocurrency Market: A Mixed Method Approach by Milad Abbasi, Somayeh Al-sadat Mousavi, Abbasali Jafari Nodoushan

“…ObjectiveThe purpose of this paper is to identify the most effective technical indicators in the cryptocurrency market, as viewed by market experts, optimize their performance using optimization algorithms, and ultimately compare the performance of the selected trading rules against each other and the buy-and-hold strategy. …”
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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

“…This paper proposes a novel hybrid approach that combines Genetic Algorithms (GA) with Long Short-Term Memory (LSTM) networks to optimize supply chain sustainability. …”
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Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

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Book Recommendation Using Collaborative Filtering Algorithm by Esmael Ahmed, Adane Letta

“…Moreover, using hyperparameter tuning with SVD also has an improvement on model performance compared with the existing SVD algorithm.…”
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Subsampling Algorithms for Irregularly Spaced Autoregressive Models by Jiaqi Liu, Ziyang Wang, HaiYing Wang, Nalini Ravishanker

“…These methods use A-optimality or D-optimality criteria to assess the usefulness of each data point and prioritize the inclusion of the most informative ones. …”
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A cloud-metaheuristic-based framework for stochastic optimization of a hybrid wind/hydrogen based-Fuel cell system in distribution network considering uncertainty by Ali S. Alghamdi

“…To effectively manage uncertainties in wind power production and network loading, the cloud model theory is employed, providing a more robust approach to handling complex stochastic variations in renewable energy optimization. An improved Fire Hawks Optimization (IFHO) algorithm is utilized in solving the optimization problem by determining the optimal installation locations and sizes of HRES components. …”
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A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

“…The primary objective was to determine the optimal monitoring period for SOC. Within this period, optimal feature subsets were extracted using variable selection algorithms. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
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Application of HHO-CNN-LSTM-based CMAQ correction model in air quality forecasting in Shanghai by ZHENG Xinnan, LIN Kaiyan, WANG Zijing, SONG Yuanbo, SHI Yang, LU Hanyue, ZHANG Yalei, SHEN Zheng*

“…Accordingly, a correction model, which combines convolutional neural network (CNN) and long-short term memory neural network (LSTM) and optimized by harris hawks optimization algorithm (HHO) was established to enhance the accuracy of CMAQ model's prediction results for six air pollutants (SO_2, NO_2, PM_10, PM_2.5, O_3 and CO). …”
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Delphi consensus statement for the management of delayed post-polypectomy bleeding by Enrique Rodríguez de Santiago, Sandra Pérez de la Iglesia, Diego de Frutos, José Carlos Marín-Gabriel, Carolina Mangas-SanJuan, Raúl Honrubia López, Hugo Uchima, Marta Aicart-Ramos, Miguel Ángel Rodríguez Gandía, Eduardo Valdivielso Cortázar, Felipe Ramos Zabala, Marco Antonio Álvarez, Marina Solano Sánchez, Jesús Manuel González Santiago, Eduardo Albéniz, Gonzalo Hijos-Mallada, Nerea Castro Quismondo, Miguel Fraile-López, David Martínez Ares, Javier Tejedor-Tejada, Luis Hernández, Joan B. Gornals, Sergi Quintana-Carbo, Juan Ocaña, João A. Cunha Neves, Juan Martínez Martínez, María López-Cerón Pinilla, Carlos Dolz Abadía, María Pellisé

“…Background: Delayed post-polypectomy bleeding (DPPB) is the most common adverse event following colonic polypectomy, yet its management remains highly heterogeneous and lacks standardization. …”
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Evaluation of geological engineering factors for productivity of deep CBM well after fracturing based on grey correlation method by KONG Xiangwei,XIE Xin,WANG Cunwu,SHI Xian

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Fleet Size and Mix Vehicle Routing Problem (FSMVRP), Adapted Large Neighbourhood Search Heuristic Optimization ProposalWith a Plant-capacity and Multi-day Planning Algorithm: A Liv... by Alperen Ekrem Çelikdin

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A Multi-Objective Particle Swarm Optimization Approach for Optimizing K-Means Clustering Centroids by Aina Latifa Riyana Putri, Joko Riyono, Christina Eni Pujiastuti, Supriyadi

“…This study evaluates the performance of the standard K-Means algorithm and proposes a Multiobjective Particle Swarm Optimization K-Means (MOPSO+K-Means) approach to improve clustering accuracy. …”
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Dynamic Sharding and Monte Carlo for Post-Quantum Blockchain Resilience by Dahhak Hajar, Nadia Afifi, Imane Hilal

“…Previous research also found that post-quantum blockchains, despite their improved cryptographic algorithms, are still vulnerable to DDoS attacks, emphasizing the need for more resilient architectural solutions. …”
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Hardware implementation of RSA encryption algorithm based on pipeline by Yang Longfei, Lu Shi, Peng Kuang

“…To address the high cost of implementing long-bits RSA encryption algorithms in hardware, improvements have been made to the traditional radix-4 Montgomery algorithm. …”
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Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…The model is designed to capture complex emotional nuances and themes in literature by processing text data from both forward and backward directions, while the attention mechanism enables the model to focus on the most important sections of the text. Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
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Optimizing Euclidean Distance Computation by Rustam Mussabayev

“…The Euclidean distance, being a computational bottleneck in large-scale optimization problems, requires efficient computation techniques to improve the performance of various distance-dependent algorithms. …”
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GaLAM: Two-Stage Outlier Detection Algorithm by Xiaojun Lu, Zhe Yan, Ziyun Fan

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Using machine learning algorithms to predict colorectal polyps by Xingjian Xiao, Shiyou Liu, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Xianglong Xu

“…Background: Colorectal cancer (CRC) is the third most common cancer worldwide, and colorectal polyps (CRP) represent a necessary pathway to the development of CRC. …”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Thus, this study has developed a novel feature-based enhanced boosting algorithm (F-EBA). The proposed model covers two pipelines, the feature engineering pipeline which improves the quality of features by picking up the most relevant features while the classification pipeline uses an ensemble approach designed to boost/elevate the model’s performances. …”
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