Natural Frequncies of Coupled Blade-Bending and Shaft-Torsional Vibrations by B.O. Al-Bedoor

“…Some results on the predicted natural frequencies are graphically presented and discussed pertinent to the coupling controlling factors and their effects. …”
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PVC failure modelling through experimental and digital image correlation measurements by Zekriti Najat, Majid Fatima, Rhanim Rajaa, Mrani Ibrahim, Rhanim Hassan

“…We investigated combined approaches focused on fracture toughness assessment to predict PVC mechanical behavior against failure. We ran a series of tests on tensile and single-edge notched samples at various crosshead speeds on a tensile test machine. …”
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Multi-Step-Ahead Forecasting Model for Monthly Anchovy Catches Based on Wavelet Analysis by Nibaldo Rodríguez, Claudio Cubillos, José-Miguel Rubio

“…In the second stage, a linear autoregressive model is constructed to predict each component and the unknown p-next values are forecasted by the addition of the two predicted components. …”
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Research on Population Development Trend in Huizhou of China Forecast Based on Optimal Weighted Combination Method and Fractional Grey Model by Dewang Li, Jianbao Chen, Meilan Qiu

“…Taking the resident population from 2008 to 2018 as the research object, the optimal weighted combination model and fractional grey model were used to study the estimated and predicted values. The results are compared and analyzed. …”
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VDB Entropy Measures and Irregularity-Based Indices for the Rectangular Kekulene System by Weidong Zhao, K. Julietraja, P. Venugopal, Xiujun Zhang

“…They are useful and cost-effective tools for predicting the properties of chemical compounds theoretically. …”
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DAMAGE IDENTIFICATION OF BEAM STRUCTURE BASED ON HYBRID NEURAL GENETIC ALGORITHM by WANG MingYue, MIAO BingRong, Li XuJuan, YANG ZhongKun

“…It has established that a crack has an important effect on the dynamic behavior of a structure.To identify the location and depth of a crack on a structure,a method is presented which uses hybrid neuro-genetic technique.This method combines genetic algorithm（GA） with neural network,and uses genetic algorithm to optimize the BP network.Though the finite element analysis,acquire the first three natural frequencies of the beam,which used as inputs into neural network models for damage assessment.Genetic algorithm（GA） optimizes the weights and thresholds of the network,and using the optimization results as the initial value of the three layer BP neural network.Though the training of the sample data,then establish the suitable network.Finally,using the theoretical natural frequencies as the test values,obtain the predicted results of crack parameters.Comparing the theoretical value with the predicted value,the results show that this algorithm can identify the damage structure accurately.…”
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Artificial Intelligence in Automotives: ANNs’ Impact on Biodiesel Engine Performance and Emissions by Ramozon Khujamberdiev, Haeng Muk Cho

“…ANNs have emerged as a vital tool in predicting and optimizing engine parameters, contributing to the enhancement of fuel efficiency and a reduction in emissions. …”
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Numerical and Analytical Modeling of Large Deflection with Local Indentation of Sandwich Beam Under Quasi-Static Transverse Loading by Mohammad Solooki

“…The present analytical model can predict the large deflection behavior with local indention of sandwich beam reasonably.…”
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Mathematical assessment of the role of temperature on desert locust population dynamics. by Dejen Ketema Mamo, Mathew N Kinyanjui, Nourridine Siewe

“…By providing a deeper understanding of temperature-driven population shifts, this model enhances the ability to predict locust outbreaks, optimize control strategies, and reduce the socio-economic and ecological impacts of locust invasions.…”
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Coordinated air-ground scheduling for UAV-assisted cell-free massive MIMO by Danhao DENG, Chaowei WANG, Fan JIANG, Weidong WANG

“…Cell-free massive multiple-input multiple-output (MIMO) technology uses a large number of access points (AP) to provide efficient communication services for terrestrial users.However, massive APs and users increase the demand for channel state information detection, especially for users with high moving speeds.In order to reduce the consumption of pilot resources, a dual system architecture that integrates unmanned aerial vehicle-assisted (UAV-assisted) communications and cell-free massive MIMO communications was proposed.The architecture was able to predict the movement trajectories of high-speed users and use UAVs to provide them with reliable communications.A UAV trajectory design and user scheduling scheme based on deep reinforcement learning (DRL) was further proposed, which maximized the system sum rate under the premise of satisfying various constraints.Simulation results demonstrate that the proposed scheme is able to predict user trajectories and improve system sum rate compared with existing schemes.…”
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Estimation of Super High-Rise Pumping Pressure for High-Performance Concrete Based on Computational Fluid Dynamics Modeling and Situation Measurement by Weijiu Cui, Chuankai Zhao, Sheng Wang

“…Traditional methods fail to predict the pumping pressure loss of high-performance concrete properly in super high-rise pumping situations due to complex changes of concrete properties. …”
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A frustratingly easy way of extracting political networks from text. by Naim Bro

“…This analysis reveals a notably stronger predictive power when sentiments are included. The findings underscore GPT-4's versatility in political network analysis.…”
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Role of Electrostatic Effects in the Pure Component and Binary Adsorption of Ethylene and Ethane in Cu-Tricarboxylate Metal-Organic Frameworks by Timothy M. Nicholson, Suresh K. Bhatia

“…Both binary GCMC simulations and Ideal Adsorbed Solution Theory predictions yielded separation factors of ca. 2 and a difference in isosteric heat of 3 kJ/mol. …”
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An adjustment method for electricity sales forecasting result considering the effects of spring festival by Jian LIU, Jiakui ZHAO, Yuze CHEN, Xuemin FANG, Yuxi LIU, Shulong WANG, Yan CHEN, Hong OUYANG

“…The effects of Spring Festival on electricity sales of different trades were considered and an adjustment method for electricity sales forecasting result was proposed.Firstly,the month-quarter ratio of historical electricity sales in each trade of every month in the first quarter and the distance between Spring Festival and the first day of every month in the first quarter was used to create a functional relationship.Then,the distance between Spring Festival and the first day of every month in the first quarter of the target year was used as input and the predicted month-quarter ratio of electricity sales of each trade of every month in the first quarter of the target year was calculated according to the functional relationship.The adjusted electricity sales forecasting result can then be computed by using the predicted month-quarter ratio and the electricity sales forecasting of each trade of every month in the first quarter of the target year before adjustment.The adjustment result shows that the proposed method can effectively lower the error of electricity sales forecasting in the first quarter.…”
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Application of Grey Self-Memory Model Based on Smoothing Method Without Seasonal Fluctuations on Monthly Runoff Forecast by WAN Yang, YANG Haiyan, TANG Jingjing

“…Affected by the monsoon climate,there are abrupt changes,non-smoothing and variation in monthly runoff.However,good accuracy cannot be realized if the monthly runoff is simulated and predicted directly by the gray self-memory model.This paper proposes a new monthly runoff smoothing method (that is,smoothing method without seasonal fluctuations).First,the seasonal index is used to remove the “seasonal fluctuations” of monthly runoff,then,the three-point smoothing method is applied to smooth the monthly runoff without seasonal fluctuations,and finally the gray self-memory model is adopted to simulate and predict the smoothed data.After being applied to the Yanling Hydrological Station in Hunan Province,the results show that the average error of fitting and forecasting value of monthly runoff after seasonal fluctuation removing and smoothing is less than 20% compared with the measured value.At the same time,the short-term monthly runoff data is used to simulate and forecast monthly runoff by this method,which also meets the requirements of the specification.…”
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Does Burnout Due to COVID-19 Affect Resilience? The Sample of Doctors in Turkiye by Aziz Bulut, Aliye Bulut, Çağla Yiğitbaş

“…This study was conducted to determine the resilience or burnout status of physicians, the characteristics that make a difference on them and whether burnout predicts resilience. Method: The study was conducted with a quantitative method and a general survey model. 246 physicians were reached in the descriptive cross-sectional study. …”
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On Curvilinear Regression Analysis via Newly Proposed Entropies for Some Benzene Models by Guangwu Liu, Muhammad Kamran Siddiqui, Shazia Manzoor, Muhammad Naeem, Douhadji Abalo

“…Other remaining physical characteristics include Gibb’s energy qℰ, logP, molar refractivity ℳℛ, and Henry’s law ℋℒ that can be predicted by using sixth ND entropy.…”
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Measuring Track-Related Pointing Errors on the Nanshan Radio Telescope with an Optical Pointing Telescope by Ye Yuan, Zhi-Yong Liu, Na Wang

“…This method uses a group of reference pointing data collected by an OPT mounted at the bottom of the antenna alidade to extract the twist effect of the alidade from the radio telescope pointing data, thus compared with the predicted twist by the track-alidade model. This method was applied to the 26 meter Nanshan Radio Telescope (NSRT 26 m), achieving good agreement with the model-predicted values.…”
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Research on Visualization of Cylindrical Gear Hobbing Cutting Force and the Influence of Cutting Parameter on Hobbing Cutting Force by Xiaoqing Tian, Xinrong Zheng, Ruofeng Chen, Jiang Han, Lian Xia

“…In order to quantify the influence of machining parameters on the cutting force in hobbing process，a method for predicting the cutting force of gear hobbing based on three-dimensional （3D） geometric simulation is studied. …”
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Customer Churn Modeling via the Grey Wolf Optimizer and Ensemble Neural Networks by Maryam Rahmaty, Amir Daneshvar, Fariba Salahi, Maryam Ebrahimi, Adel Pourghader Chobar

“…In recent years, many methods have been developed including data mining for predicting the customer churn and manners that customers are likely to behave in the future and therefore, taking action early to prevent their leaving. …”
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