Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools
Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …
Traffic sensor location problem: Three decades of research
Traffic flow data is a decisive element in transportation planning and traffic management.
Over time, traffic sensors have been recognized as sources of such data. Despite their …
Over time, traffic sensors have been recognized as sources of such data. Despite their …
Multilevel threshold image segmentation for COVID-19 chest radiography: A framework using horizontal and vertical multiverse optimization
COVID-19 is currently raging worldwide, with more patients being diagnosed every day. It
usually is diagnosed by examining pathological photographs of the patient's lungs. There is …
usually is diagnosed by examining pathological photographs of the patient's lungs. There is …
ConvUNeXt: An efficient convolution neural network for medical image segmentation
Recently, ConvNeXts constructing from standard ConvNet modules has produced
competitive performance in various image applications. In this paper, an efficient model …
competitive performance in various image applications. In this paper, an efficient model …
Simulated annealing-based dynamic step shuffled frog lea** algorithm: Optimal performance design and feature selection
The shuffled frog lea** algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …
combinatorial optimization problem, which effectively combines the memetic algorithm …
Evaluating the performance of various algorithms for wind energy optimization: a hybrid decision-making model
Wind resource is one of the most promising renewable energy, which has become a suitable
replacement for fossil fuels. Optimizing the transferring wind energy from a wind turbine is …
replacement for fossil fuels. Optimizing the transferring wind energy from a wind turbine is …
An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems
The sine cosine algorithm (SCA) is a well-known meta-heuristic optimization algorithm. SCA
has received much attention in various optimization fields due to its simple structure and …
has received much attention in various optimization fields due to its simple structure and …
Quadratic interpolation and a new local search approach to improve particle swarm optimization: Solar photovoltaic parameter estimation
Abstract The Particle Swarm Optimization technique (PSO) is widely used in practical
applications due to its flexibility and strong optimization performance. However, like other …
applications due to its flexibility and strong optimization performance. However, like other …
Divergence measures for circular intuitionistic fuzzy sets and their applications
Abstract Circular Intuitionistic Fuzzy Set (C-IFS) is the real extension of the standard
Intuitionistic Fuzzy Sets (IFS), where each element is represented by a circle instead of a …
Intuitionistic Fuzzy Sets (IFS), where each element is represented by a circle instead of a …
Information sharing search boosted whale optimizer with Nelder-Mead simplex for parameter estimation of photovoltaic models
L Peng, C He, AA Heidari, Q Zhang, H Chen… - Energy Conversion and …, 2022 - Elsevier
With the recent emphasis on new energy sources, solar photovoltaic cells have received
widespread attention from scholars as a highly efficient and clean new energy source …
widespread attention from scholars as a highly efficient and clean new energy source …