AI Medical Compendium Journal:
Mathematical biosciences and engineering : MBE

Showing 41 to 50 of 288 articles

Complex pythagorean fuzzy aggregation operators based on confidence levels and their applications.

Mathematical biosciences and engineering : MBE
The most important influence of this assessment is to analyze some new operational laws based on confidential levels (CLs) for complex Pythagorean fuzzy (CPF) settings. Moreover, to demonstrate the closeness between finite numbers of alternatives, th...

Effect of dual-convolutional neural network model fusion for Aluminum profile surface defects classification and recognition.

Mathematical biosciences and engineering : MBE
Classifying and identifying surface defects is essential during the production and use of aluminum profiles. Recently, the dual-convolutional neural network(CNN) model fusion framework has shown promising performance for defects classification and re...

Federated personalized random forest for human activity recognition.

Mathematical biosciences and engineering : MBE
User data usually exists in the organization or own local equipment in the form of data island. It is difficult to collect these data to train better machine learning models because of the General Data Protection Regulation (GDPR) and other laws. The...

Analysis of medical diagnosis based on variation co-efficient similarity measures under picture hesitant fuzzy sets and their application.

Mathematical biosciences and engineering : MBE
One of the most dominant and feasible technique is called the PHF setting is exist in the circumstances of fuzzy set theory for handling intricate and vague data in genuine life scenario. The perception of PHF setting is massive universal is compared...

Fuzzy-interval inequalities for generalized preinvex fuzzy interval valued functions.

Mathematical biosciences and engineering : MBE
In this paper, firstly we define the concept of -preinvex fuzzy-interval-valued functions (-preinvex FIVF). Secondly, some new Hermite-Hadamard type inequalities (- type inequalities) for -preinvex FIVFs via fuzzy integrals are established by means o...

Reinforcement learning-based optimization of locomotion controller using multiple coupled CPG oscillators for elongated undulating fin propulsion.

Mathematical biosciences and engineering : MBE
This article proposes a locomotion controller inspired by black Knifefish for undulating elongated fin robot. The proposed controller is built by a modified CPG network using sixteen coupled Hopf oscillators with the feedback of the angle of each fin...

A novel design of Gudermannian function as a neural network for the singular nonlinear delayed, prediction and pantograph differential models.

Mathematical biosciences and engineering : MBE
The present work is to solve the nonlinear singular models using the framework of the stochastic computing approaches. The purpose of these investigations is not only focused to solve the singular models, but the solution of these models will be pres...

A Bio-inspired trajectory planning method for robotic manipulators based on improved bacteria foraging optimization algorithm and tau theory.

Mathematical biosciences and engineering : MBE
In this paper, a novel bio-inspired trajectory planning method is proposed for robotic systems based on an improved bacteria foraging optimization algorithm (IBFOA) and an improved intrinsic Tau jerk (named Tau-J*) guidance strategy. Besides, the ada...

Training method and system for stress management and mental health care of managers based on deep learning.

Mathematical biosciences and engineering : MBE
In recent years, with the rapid development of the economy, in order to stabilize in the market and expand their own business, various companies in the form of various indicators, tangible or intangible to improve the management of the work of worker...

Numerical investigations of the nonlinear smoke model using the Gudermannian neural networks.

Mathematical biosciences and engineering : MBE
These investigations are to find the numerical solutions of the nonlinear smoke model to exploit a stochastic framework called gudermannian neural works (GNNs) along with the optimization procedures of global/local search terminologies based genetic ...