Results 111 to 120 of about 4,246 (160)

ACO-optimized MobileNetV2-ShuffleNet hybrid model for automated dental caries classification. [PDF]

Sci Rep
Kaveri K, K VRP, Reddy GP, Pothamsetti SLG, Radha K, Penumaka R.   +5 more
europepmc   +1 more source

Applying the Ensemble and Metaheuristic Algorithm to Predict the Flexural Characteristics of Ice. [PDF]

Materials (Basel)
Lu C, Han X.
europepmc   +1 more source

Optimization of New Cropland Allocation to Enhance Stable Utilization Potential: A Case Study of Guangdong Province, China. [PDF]

Foods
Zhao L, Qiao Z, Liu G, Wang H.
europepmc   +1 more source

Adjusted Rand Index-Guided DPSO for Clustering and Data Routing in Wireless Sensor Networks. [PDF]

Sensors (Basel)
Mohi Dine SM, Zhu Z, Finnerty P, Ohta C.
europepmc   +1 more source

PhishNet 1.0: optuna-optimized stacking ensemble with Boruta-based feature selection for phishing URL detection. [PDF]

Sci Rep
Jain A, Khan S, Koli K, Taneja H, Panwar A, Alshammari T, Obaid EM, Abdu SM.   +7 more
europepmc   +1 more source

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Pheromone models in ant colony optimization (ACO)

Journal of Interdisciplinary Mathematics, 2006
Ant Colony Optimization is a constructive meta-heuristic that uses an analogue of ant trail pheromones to learn about good features of solutions. In this paper, using the difference equations as a tool of research, we propose the mathematical model of the distribution of pheromone at the classic double bridge experiment, explain the mathematical model ...
E. Foundas, A. Vlachos
exaly   +2 more sources

Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment

Applied Soft Computing Journal, 2008
Multiple sequence alignment, known as NP-complete problem, is among the most important and challenging tasks in computational biology. For multiple sequence alignment, it is difficult to solve this type of problems directly and always results in exponential complexity.
Shun-Feng Su, Zne-Jung Lee, Chen-Chia Chuang   +2 more
exaly   +2 more sources

A comprehensive study: Ant Colony Optimization (ACO) for facility layout problem

2017 16th RoEduNet Conference: Networking in Education and Research (RoEduNet), 2017
In context of manufacturing, numerous models are designed to appropriately represent the facility layout problem (FLP) and a variety of optimization methods have been applied to solve these models. The ultimate goal of these methods is to find optimal solutions, In regard to Swarm Intelligence (SI), Ant Colony Optimization (ACO) and Particle Swarm ...
Raed Abdulkareem Hasan, Mostafa Abdulghafoor Mohammed, Nicolae Tapus, Omar Abdulmaged Hammood   +3 more
openaire   +1 more source

Ant Colony Optimization (ACO)

2013
The ant colony optimization algorithm (ACO) is an evolutionary meta-heuristic algorithm based on a graph representation that has been applied successfully to solve various hard combinatorial optimization problems. Initially proposed by Marco Dorigo in 1992 in his PhD thesis [49], the main idea of ACO is to model the problem as the search for a minimum ...
Muhammet Ünal, Ayça Ak, Vedat Topuz, Hasan Erdal   +3 more
openaire   +1 more source