-
121
-
122
AI-Driven Optimization of Blockchain Scalability, Security, and Privacy Protection
Published 2025-05-01“…Artificial intelligence, with its powerful data processing capability, pattern recognition ability, and adaptive optimization algorithms, can improve the transaction processing efficiency of blockchain, enhance the security mechanism, and optimize the privacy protection strategy, thus effectively alleviating the limitations of blockchain in terms of scalability and security. …”
Get full text
Article -
123
Optimal policy for composite sensing with crowdsourcing
Published 2020-05-01“…The solution includes optimal and myopic policies. Besides, we provide necessary theoretical analysis, which ensures the optimality of the optimal algorithm. …”
Get full text
Article -
124
Hardware reconfigurable coding and evolution algorithm based on evolvable hardware
Published 2012-08-01“…A planar mapping function increments chromosome coding method based on FPGA platform with SRAM-architecture was proposed.The method could improve hardware reconfiguration efficiency by coding mapping realized by double platform mapping of binary configurable file string.Meanwhile,a betterment difference evolution algorithm was proposed based on local optimal mechanism introduced.The algorithm could promote convergence rate and whole efficiency.Finally,the result of the algorithm emulation shows that:MDE improves disadvantage of difference evolution algorithm with local optimal and approaches actual optimization outcome.…”
Get full text
Article -
125
-
126
Hierarchical multi step Gray Wolf optimization algorithm for energy systems optimization
Published 2025-03-01“…Abstract Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in various domains, including engineering design, image processing, and machine learning. …”
Get full text
Article -
127
Stochastic Block-Coordinate Gradient Projection Algorithms for Submodular Maximization
Published 2018-01-01“…We consider a stochastic continuous submodular huge-scale optimization problem, which arises naturally in many applications such as machine learning. …”
Get full text
Article -
128
Specifics of the Algorithmic Prescriptions in the Learning Process of the Gymnastics Exercises’ Techniques
Published 2025-03-01“… The technology of training gymnastic exercises demonstrates a series of groupings of the most rational and optimal methods; however, the algorithmic type prescriptions are considered the closest to the effective achievement of the theoretical-methodological and practical objectives (in order to acquire the technique of gymnastic exercises with an increased degree of difficulty). …”
Get full text
Article -
129
Multi-Feature Facial Complexion Classification Algorithms Based on CNN
Published 2025-06-01“…The optimal approach combining multi-feature CNN with machine learning algorithms attains a remarkable accuracy of 97.78%. …”
Get full text
Article -
130
On the Effectiveness of the Minimization Approach to the Query Optimization
Published 2016-04-01“…In the end, we represent an observation of the query minimization impact on the whole optimization process…”
Get full text
Article -
131
Improved grey wolf optimization algorithm based service function chain mapping algorithm
Published 2022-11-01“…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
Get full text
Article -
132
Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm.
Published 2024-01-01“…In particular, the wrapper algorithm is an improved Grey Wolf Optimization (IGWO) algorithm based on random disturbance factors, while the parameters are adjusted to vary randomly to make the population variations rich in diversity. …”
Get full text
Article -
133
Multiplier leadership optimization algorithm (MLOA): unconstrained global optimization approach for melanoma classification
Published 2025-06-01“…Abstract This paper proposes the multiplier leadership optimization algorithm, which draws inspiration from multiplier leadership principles to search for and optimize solutions to complex problems effectively. …”
Get full text
Article -
134
Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm
Published 2025-05-01“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
Get full text
Article -
135
A new human-based offensive defensive optimization algorithm for solving optimization problems
Published 2025-04-01“…Abstract A novel human-inspired metaheuristic algorithm, termed Offensive Defensive Optimization, has been introduced to address single-objective optimization problems. …”
Get full text
Article -
136
Comparative Review of Multi-Objective Optimization Algorithms for Design and Safety Optimization in Electric Vehicles
Published 2024-01-01“…Despite the widespread use of established optimization algorithms like Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), Non-Dominated Sorting Genetic Algorithm-III (NSGA-III), and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) in real-world engineering optimization problems, newer algorithms such as Two-Stage NSGA-II (TS-NSGA-II), Dynamic Constrained NSGA-III (DCNSGA-III), MOEA/D with Virtual Objective Vectors (MOEA/D-VOV), Large-Scale Evolutionary Multi-Objective Optimization Assisted by Directed Sampling (LMOEA-DS), and Super-Large-Scale Multi-Objective Evolutionary Algorithm (SLMEA) remain underexplored in the context of Battery Electric Vehicle (BEV) safety, particularly in optimizing complex, non-linear, and constrained multi-objective problems like crashworthiness and thermal management. …”
Get full text
Article -
137
Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm
Published 2025-05-01“…Finally, the Nondominated Sorting Genetic Algorithm II (NSGA-II) was used to optimize the urea injection volume for all conditions. …”
Get full text
Article -
138
RRT-Based Optimizer: A Novel Metaheuristic Algorithm Based on Rapidly-Exploring Random Trees Algorithm
Published 2025-01-01“…Real-world optimization problems are becoming increasingly complex and require effective and versatile algorithms to provide reliable solutions. …”
Get full text
Article -
139
Portfolio Optimization with Artificial Hummingbird Algorithm for Cement Industry
Published 2024-12-01“…Portfolio optimization, which is performed while investing in any asset, is an important issue for all investors and finance researchers. …”
Get full text
Article -
140
An optimal L∞-PLA algorithm for trajectory data compression
Published 2024-09-01“…MDisPLA used a divide-and-conquer strategy to extend the one-dimensional optimal PLA algorithm for optimizing compression of multi-dimensional trajectory data. …”
Get full text
Article