Two-Stage Learning of CPG and Postural Reflex Toward Quadruped Locomotion on Uneven Terrain With Simple Reward by Ryosei Seto, Guanda Li, Kyo Kutsuzawa, Dai Owaki, Mitsuhiro Hayashibe

“…Among them, the Central Pattern Generator-Reinforcement Learning (CPG-RL) framework, which combines Central Pattern Generators (CPG) with reinforcement learning (RL), offers key advantages such as accelerated learning, improved Sim-to-Real transfer, and the ability to learn with a simplified reward function. …”
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Inferential analysis of the stress-strength reliability for a new extended family of distributions by Mohammed S. Kotb, Mohammed Z. Raqab

“…We propose estimators, including the maximum likelihood and Bayes estimators, as well as various confidence and credible intervals for both the unknown parameters and R, utilizing conjugate priors. In a Bayesian context, we use importance sampling within the Metropolis-Hastings sampler for parameter and reliability function estimation. …”
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Neutrosophic Quasi-XLindley distribution with applications of COVID-19 data by Rehab Alsultan, Amer Ibrahim Al-Omari

“…In this study, we present some statistical characteristics of the NQXL distribution, including the neutrosophic mean time failure, neutrosophic hazard rate, neutrosophic moments, and neutrosophic survival function. We also evaluate the parameters using the maximum likelihood (ML) estimation technique in a neutrosophic context based on a simulation study. …”
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The Study of Fractional Order Controller with SLAM in the Humanoid Robot by Shuhuan Wen, Xiao Chen, Yongsheng Zhao, Ahmad B. Rad, Kamal Mohammed Othman, Ethan Zhang

“…We can discretize the transfer function by the Al-Alaoui generating function and then get the FOPI controller by Power Series Expansion (PSE). …”
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Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method by Lijuan Zhang, Dongming Li, Wei Su, Jinhua Yang, Yutong Jiang

“…Secondly, the EM algorithm is improved by combining the AO imaging system parameters and regularization technique. A cost function for the joint-deconvolution multiframe AO images is given, and the optimization model for their parameter estimations is built. …”
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Energy-Efficient and Fault-Tolerant Control of a Six-Axis Robot Based on AI Models by Patryk Nowak, Zoran Pandilov

“…Specifically, a genetic algorithm is used to generate learning data for the selection of the optimal kinematic configuration of the robot, and a multilayer perceptron is utilized to predict the parameters of the defined reward function. This function is crucial for selecting the optimal action at each time step. …”
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Multivariate Modified Dugum Distribution and Its Applications by Naelah Alghufily, Khalaf S. Sultan, Hossam M. M. Radwan

“…Further, we use the maximum likelihood method to estimate the unknown parameters and the associated confidence interval. Finally, we apply the proposed model to analyze some real data sets, including a protein consumption data set and a warranty policy data set, for demonstrative purposes. …”
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Six-wave interaction on resonant nonlinearity in a waveguide with infinitely conducting surfaces by Valery V. Ivakhnik, Darkhan R. Kapizov, Vladimir I. Nikonov

“…When using six-wave radiation converters implemented in waveguides, in nonlinear adaptive optics systems, real-time image processing, it is necessary to know the correspondence between the complex amplitudes of the signal and object waves. …”
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Closed-Loop Supply Chain Network Design under Uncertainties Using Fuzzy Decision Making by Zhengyang Hu, Viren Parwani, Guiping Hu

“…The original formulation with uncertain parameters is firstly converted into a crisp model and then an aggregation function is applied to combine the objective functions. …”
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Efecto de los coeficientes de aceleración de PSO en el desempeño de una Red Neuronal Artificial aplicada a la Estimación de Costos by Elba Bodero Poveda, Guillermo Leguizamón

“…The objective function used is the Mean Square Error (MSE), calculated between the observed values and the values estimated by the ANN. …”
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Studying the Role of Personality Traits on the Evacuation Choice Behavior Pattern in Urban Road Network in Different Severity Scales of Natural Disaster by Fatemeh Mohajeri, Babak Mirbaha

“…By considering these variables as random parameters, the Log Likelihood function and pseudo square (ρ2) of the model increased.…”
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Competing Risks Failure Model Under Progressive Censoring With Random Removals Based on the Generalized Power Half Logistic Geometric Distribution by Ahlam H. Tolba, Ahmed Ramses El-Saeed

“…We consider the removal of subjects at each failure time according to a binomial distribution with known parameters. Both classical and Bayesian approaches facilitate point- and interval-estimation procedures for parameters and parametric functions. …”
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Identification of the Mathematical Model of Tuberculosis and HIV Co-Infection Dynamics by Sergey Kabanikhin, Olga Krivorotko, Andrei Neverov, Grigoriy Kaminskiy, Olga Semenova

“…A sensitivity-based identifiability analysis of this mathematical model was performed, which revealed the sensitivity of the averaged parameters of the models to statistical real data of infectious individuals based on the Sobol method. …”
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Simple and Versatile Dynamic Model of Spherical Roller Bearing by Behnam Ghalamchi, Jussi Sopanen, Aki Mikkola

“…In the model, bearing forces and deflections were calculated as a function of contact deformation and bearing geometry parameters according to the nonlinear Hertzian contact theory. …”
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N-order solutions to the Gardner equation in terms of Wronskians by Pierre Gaillard

“…$N$-order solutions to the Gardner equation (G) are given in terms of Wronskians of order $N$ depending on $2N$ real parameters. We get solutions expressed with trigonometric or hyperbolic functions. …”
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Atrial fibrillation reduces CSF flow dynamics. A multimodal MRI study by Sabine Hofer, Marlena Schnieder, Leonie Polster, Peter Dechent, Mathias Bähr

“…Thus, our aim was to examine GS function in AF using a fast multimodal imaging protocol in a single MRI session. …”
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ESTIMATION OF DECREASING LOSSES OF ACTIVE POWER IN TRANSFORMERS IN SETTING BATTERY OF LOW-VOLTAGE CAPACITORS by V. N. Radkevich, M. N. Tarasova

“…It is established that decreasing of losses of active power depends on technical parameters and load factor of transformer, coefficient of loading power of electricity consumers, voltage value connected to capacitor unit.Using obtained functional dependences, calculations for the main size-types of power transformers with voltage 10(6)/0,4 kV serie ТМГ 11 and ТМГ12 were done. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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Two-Dimensional Probability Models for the Weighted Discretized Fréchet–Weibull Random Variable with Min–Max Operators: Mathematical Theory and Statistical Goodness-of-Fit Analysis... by Sofian T. Obeidat, Diksha Das, Mohamed S. Eliwa, Bhanita Das, Partha Jyoti Hazarika, Wael W. Mohammed

“…Additionally, key statistical measures, including covariance, Pearson’s correlation coefficient, Spearman’s rho, and Kendall’s tau, are derived using the joint probability-generating function. For robust statistical inferences, the parameters of the proposed models are estimated via the maximum likelihood estimation method, with extensive simulation studies conducted to assess the efficiency and accuracy of the estimators. …”
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Dynamic Peak Threshold Estimation Method for Noise Mitigation in Hybrid PLC/VLC Systems by Irvine Mapfumo, Thokozani Shongwe

“…However, it is important to acknowledge that it is extremely difficult to determine such parameters in real-life applications due to the dynamic nature of impulsive noise. …”
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