Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…When a fault occurs in the distribution network, the sensor device based on optimal configuration collects fault feature data, combines it with the FCM clustering algorithm to classify nodes according to fault feature similarity, and divides the most significant fault-affected section as the core fault area. …”
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Enhanced Transmission Expansion Planning With a High Confidence Strategy Considering Fluctuations in Solar PV Generation and Electricity Demand by Siripat Somchit, Niphon Kaewdornhan, Rongrit Chatthaworn

“…To address this issue, this work proposes an enhanced TEP-based 24-hour situation optimized by an improved Binary Differential Evolution (BDE) algorithm assisted by the logistic map for adjusting the mutation factor and crossover rate. …”
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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

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Robust dispatch for electrical–thermal combined smart building considering impacts of uncertainties on thermal side by Weijie He, Fanrong Wei, Xiangning Lin, Samir M. Dawoud

“…To deal with the nonlinearity brought by the electrical–thermal coupled relationship, we propose a piecewise linearization method to convert the nonlinear robust co-optimization dispatch to a linear min–max–min problem, which can be solved by a traditional decomposition algorithm. …”
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Comparative analysis of machine learning models for the detection of fraudulent banking transactions by Pedro María Preciado Martínez, Ricardo Francisco Reier Forradellas, Luis Miguel Garay Gallastegui, Sergio Luis Náñez Alonso

“…The aim is to evaluate and determine the most effective model for identifying suspicious transactions, overcoming the challenge of a highly imbalanced dataset. …”
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Let’s get in sync: current standing and future of AI-based detection of patient-ventilator asynchrony by Thijs P. Rietveld, Björn J. P. van der Ster, Abraham Schoe, Henrik Endeman, Anton Balakirev, Daria Kozlova, Diederik A. M. P. J. Gommers, Annemijn H. Jonkman

“…Results of algorithms are generally promising (average reported sensitivity, specificity and accuracy of 0.80, 0.93 and 0.92, respectively), but most algorithms are only available offline, can detect a small subset of PVAs (focusing mostly on ineffective effort and double trigger asynchronies), or remain in the development or validation stage (84% (16/19 of the reviewed studies)). …”
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Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

“…The experimental results show that compared to the single skill model, this model can effectively shorten project duration, reduce human resource costs, and improve skill scores. For example, in a specific experimental dataset, when the project duration is limited to 200 h, the most suitable labor duration for the plan is 193.8 h, the human resource cost is 7493 yuan, and the skill score is improved by 268. …”
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Leanness Computation: Small Values and Special Graph Classes by David Coudert, Samuel Coulomb, Guillaume Ducoffe

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Full-Waveform Inversion of Two-Parameter Ground-Penetrating Radar Based on Quadratic Wasserstein Distance by Kai Lu, Yibo Wang, Heting Han, Shichao Zhong, Yikang Zheng

“…In this study, the Wasserstein distance is computed by using entropy regularization and the Sinkhorn algorithm to reduce computational complexity and improve efficiency. …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…Following this, feature selection uses the African Buffalo Optimization with Decision Tree (ABO-DT) method. This nature-inspired metaheuristic algorithm imitates the behaviour of African buffalos to determine which traits are the most important. …”
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A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…The proposed model employs an improved Squirrel Search Algorithm-based Feature Selection (ISSA-FS) to identify the most relevant features from medical data. …”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno–economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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Decentralized Voltage and Var Control of Active Distribution Network Based on Parameter-Sharing Deep Reinforcement Learning by Binqiao Zhang, Changlin He

“…The more renewable energies are integrated, the more Active Distribution Networks (ADNs) are at risk of instability. Most optimization techniques depend on accurate uncertainty models and take a long time to produce results. …”
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Navigating Intelligence: A Survey of Google OR‐Tools and Machine Learning for Global Path Planning in Autonomous Vehicles by Alexandre Benoit, Pedram Asef

“…GPP is essential for ROMIE's optimal performance, which is translated into solving the traveling salesman problem, a complex graph theory challenge that is crucial for determining the most effective route to cover all sampling locations in a mining field. …”
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Advanced clustering and transfer learning based approach for rice leaf disease segmentation and classification by Samia Nawaz Yousafzai, Fahd N. Al-Wesabi, Hadeel Alsolai, Shouki A. Ebad, Inzamam Mashood Nasir, Emad Fadhal, Adel Thaljaoui

“…Also, the tent chaotic particle snow ablation optimizer is added into the learning process in order to improve the learning process and shorten the time of convergence. …”
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Pricing principles in the field of ready–made meal delivery: analysis of influence factors by K. V. Martynov

“…The study describes the most popular pricing principles: cost–based, competitor–oriented, as well as dynamic algorithms taking into account seasonal demand. …”
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Training multi-layer binary neural networks with random local binary error signals by Luca Colombo, Fabrizio Pittorino, Manuel Roveri

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Enhancing Wind Turbine Efficiency: An Experimental Investigation of a Sensorless Three-Vector Finite Set Predictive Torque Control Approach for PMSG-Based Systems by Marouane Ahmed Ghodbane, Toufik Mohamed Benchouia, Mohamed Chebaani, Mohamed Becherif, Yassine Himeur, Amar Golea, Abdelmoumen Ghilani, Zakaria Alili, Shadi Atalla, Wathiq Mansoor

“…This approach does not require an anemometer, mechanical parameters, or rotor position sensors, making the system simpler, more reliable, and cost-effective. The 3V FS-PTC algorithm enhances control performance by selecting the three most optimal voltage vectors, two active voltage vectors and one zero voltage vector. …”
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An intelligent attention based deep convoluted learning (IADCL) model for smart healthcare security by J. Maruthupandi, S. Sivakumar, B. Lakshmi Dhevi, S. Prasanna, R. Karpaga Priya, Shitharth Selvarajan

“…Afterwards, optimization in the classification process is done by the SA-HHO algorithm, which provides the optimal weight values. …”
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Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions by Oğuzhan Timur, Bayram Kaan Uzundağ

“…The partial shading of PV modules is one of the most crucial factors that causes the performance degradation of PV systems. …”
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