Advancing Spike Sorting Through Gradient‐Based Preprocessing and Nonlinear Reduction With Agglomerative Clustering by Mohammad Amin Lotfi, Fatemeh Zareayan Jahromy, Mohammad Reza Daliri

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Flow Shop Scheduling Using a Combination of Ant Colony Optimization Algorithm and Tabu Search Algorithm to Minimize Total Tardiness by Hana Merlina Hesti Bestari, Pratya Poeri Suryadhini, Nopendri Nopendri

“…At the same time, the Tabu Search algorithm is applied as a local search to improve the quality of the solution found by ACO. …”
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Forecasting Models and Genetic Algorithms for Researching and Designing Photovoltaic Systems to Deliver Autonomous Power Supply for Residential Consumers by Ekaterina Gospodinova, Dimitar Nenov

“…This model can be used with a genetic algorithm to make a prediction that fits a specific case, such as a time series representation based on discrete fuzzy sets of the second type. …”
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An Oracle Normalized Least Mean Square (NLMS) Algorithm and a Simple Bayesian Detection NLMS Algorithm Robust to Impulse Noise by Hadi Zayyani, Yaser Attar

“…This paper suggests an oracle normalized least-mean-square (NLMS) algorithm and a simple Bayesian detection NLMS impulse noise detection algorithm as an effective adaptive algorithm against impulsive noises. …”
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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

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18F-FDG dose reduction using deep learning-based PET reconstruction by Ryuji Akita, Komei Takauchi, Mana Ishibashi, Shota Kondo, Shogo Ono, Kazushi Yokomachi, Yusuke Ochi, Masao Kiguchi, Hidenori Mitani, Yuko Nakamura, Kazuo Awai

“…Compared to the recommended dose in the European Association of Nuclear Medicine (EANM) guidelines for 90 s per bed position (4.7 MBq/kg), this represents a dose reduction of 36%. Further optimization of DLR algorithms is required to maintain comparable diagnostic accuracy in patients weighing 75 kg or more.…”
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New Algorithm of Stress Echocardiography with Adenosine Triphosphate by N. Yu. Nelassov, M. N. Morgunov, R. V. Sidorov, N. S. Doltmurzieva, O. L. Eroshenko, E. A. Arzumanjan, E. L. Kreneva, S. V. Shlyk

“…The key provisions of the new algorithm were: (a) the exercise test consisted of 3 stages (EchoCG data should be recorded before, during, and 5 minutes after ATP infusion); (b) the criterion for achieving submaximal myocardial hyperemia during ATP administration is a systolic blood pressure (SBP) reduction of 5 and more mm Hg; (c) EchoCG was usually recorded at Stage 2 of the test 3 minutes after the start of ATP administration and with a decline in SBP; (d) the initial dose of ATP administration was 140 pg/kg/min; if SBP did not decrease at 3 minutes of the drug administration, the dosage should be first increased up to 175 pg/kg/ min at 1 minute; if there was no effect, the dosage should be increased up to 210 pg/kg/min at another 2-3 minutes. …”
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Fiber-Optic Sensor Spectrum Noise Reduction Based on a Generative Adversarial Network by Yujie Lu, Qingbin Du, Ruijia Zhang, Bo Wang, Zigeng Liu, Qizhe Tang, Pan Dai, Xiangxiang Fan, Chun Huang

“…Additionally, the proposed algorithm was tested for multimode noise reduction, demonstrating an excellent linearity in temperature response with a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 99.95% for its linear fitting and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>99.74</mn><mo>%</mo></mrow></semantics></math></inline-formula> for the temperature response obtained from single-mode fiber sensors. …”
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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

Subjects: “…Gravity search optimization algorithm…”
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Predicting equilibrium scour depth around non-circular bridge piers with shallow foundations using hybrid explainable machine learning methods by Nasrin Eini, Saeid Janizadeh, Sayed M. Bateni, Changhyun Jun, Essam Heggy, Marek Kirs

“…This study combines two metaheuristic optimization techniques—Siberian tiger optimization (STO) and brown-bear optimization algorithms (BOA)—with artificial neural networks (ANNs) to enhance deq prediction accuracy for both round- and sharp-nosed piers using both field and laboratory data. …”
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RTRS algorithm in low-power Internet of things by Yuchen CHEN, Yuan CAO, Laipeng ZHANG, Lianghui DING, Feng YANG

“…Considering the feature of periodical uplink data transmission in IEEE 802.11ah low-power wide area network (LWPAN),a real-time RAW setting (RTRS) algorithm was proposed.Multiple node send data to an access point (AP),and the uplink channel resources were divided into Beacon periods in time.During a Beacon period,AP firstly predicted the next data uploading time and the total amount of devices that will upload data in the next Beacon period.The AP calculated the optimal RAW parameters for minimum energy cost and broadcasted the information to all node.Then all devices upload data according to the RAW scheduling.The simulation results show that the current network state can be predicted accurately according to the upload time of the terminal in the last period.According to the predicted state,raw configuration parameters can be dynamically adjusted and the energy efficiency can be significantly improved.…”
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RTRS algorithm in low-power Internet of things by Yuchen CHEN, Yuan CAO, Laipeng ZHANG, Lianghui DING, Feng YANG

“…Considering the feature of periodical uplink data transmission in IEEE 802.11ah low-power wide area network (LWPAN),a real-time RAW setting (RTRS) algorithm was proposed.Multiple node send data to an access point (AP),and the uplink channel resources were divided into Beacon periods in time.During a Beacon period,AP firstly predicted the next data uploading time and the total amount of devices that will upload data in the next Beacon period.The AP calculated the optimal RAW parameters for minimum energy cost and broadcasted the information to all node.Then all devices upload data according to the RAW scheduling.The simulation results show that the current network state can be predicted accurately according to the upload time of the terminal in the last period.According to the predicted state,raw configuration parameters can be dynamically adjusted and the energy efficiency can be significantly improved.…”
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Predictable and non-stationary processes of interval PREDICTION BASED ON stochastic differential equations by A. V. Ausiannikau

“…Predictability of such processes is defined. Algorithms of interval prediction in the discrete and continuous time are received.…”
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Generating diversity and securing completeness in algorithmic retrosynthesis by Florian Mrugalla, Christopher Franz, Yannic Alber, Georg Mogk, Martín Villalba, Thomas Mrziglod, Kevin Schewior

“…In this work we focus on algorithms for assembling such predictions to a full synthesis plan that, starting from simple building blocks, produces a given target molecule, a procedure known as retrosynthesis. …”
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Exposing Optimal Feature Sets for Enhancing Machine Learning Performance by Hiba Mohammed Al-Marwai, Ghaleb H. Al-Gaphari, Mohammed Mohammed Zayed

Subjects: “…Crow search algorithm…”
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Influence of Using ACO Algorithm in STATCOM Performance by Maha Al-Flaiyeh

“…In  (STATCOM) there are two control loop, the inner loop which is represented by controlling the source current, and the outer loop which is used to control the voltage of the  DC-link energy –storage- capacitor (vdc). Many algorithms are used in optimization to predict a specific behavior and to find the best solution for it. …”
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Stochastic Explicit Calibration Algorithm for Survival Models by Jeongho Park, Sangwook Kang, Gwangsu Kim

“…In this study, we introduce Stochastic Explicit Calibration (S-cal), an algorithm that employs random intervals instead of fixed bins, thereby advancing the calibration methods used in deep networks. …”
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Multidimensional State Data Reduction and Evaluation of College Students’ Mental Health Based on SVM by Han Peiqing

“…In response to the shortcomings of the traditional methods for evaluating the mental health status of college students in terms of computational complexity and low accuracy, a method for evaluating the mental health status of college students based on data reduction and support vector machines was proposed. …”
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Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms by P. V. Matrenin, A. I. Khalyasmaa, V. V. Gamaley, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski, Y. V. Potachits

“…For this, it is also proposed to use studied the feature space dimensionality reduction algorithm to visualize and estimate the clustering accuracy. …”
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Focus on Disaster Risk Reduction by ResNet-CDMV Model After Natural Disasters by Zhaojia Tang, Yu Han

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