Torthaí cuardaigh - optimization algorithm

In this study, we have explored and discussed the data mining-based solutions to apparel size assignment using approach principle, K-means clustering, and support vector machine, respectively. A case of mass customization for men's pants in China with 200 adult males were employed to validate a...

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This paper represents an efficient model for heart disease prediction model utilizing an ensemble mechanism optimized through BAT algorithm. Worldwide mortality rates are widely acknowledged to be significantly influenced by the prevalence of cardiovascular disease, particularly in economically dis...

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The majority of high dimensional gene expression data contain a significant amount of redundant genes, posing challenges for machine learning algorithms due to their high dimensionality. Feature selection has shown to be a successful method for improving classification algorithms performance by addr...

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In today's technology-driven decision-making era, there is a growing demand for methodical solutions that leverage hybrid nature-inspired protocols with deep learning models (DLM). An evolution in data management through structured systems is essential. We propose a revolutionary method that co...

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This paper presents a comparative analysis between classical maximum flow algorithms and modern deep Reinforcement Learning (RL) algorithms applied to traffic optimization in urban environments. Through SUMO simulations and statistical tests, algorithms such as Ford–Fulkerson, Edmonds–Karp, Dinitz,...

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The physical problem of element yield inversion is transformed into a mathematical problem of solving overdetermined equations, then the particle swarm optimization algorithm is used to find the optimal solution of the system of equations to obtain the yield of formation elements. During th...

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In the design process of a photovoltaic (PV) power plant, determination of the maximum power that can be extracted from the PV modules is essential, especially for the dimensioning of the individual parts of the plant. This paper presents the determination of the maximum power point (MPPT) of a bifa...

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Tuning PID controllers to enhance longitudinal control and speed planning of Electric Autonomous Vehicles is a challenge, which can be effectively addressed by evolving metaheuristic algorithms. This paper evaluates the performance of the Jellyfish Search (JS) optimizer and Genetic Algorith...

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Abstract BackgroundTraditional ocular gaze photograph preprocessing, relying on manual cropping and head tilt correction, is time-consuming and inconsistent, limiting artificial intelligence (AI) model development and clinical application. ObjectiveThis study aimed...

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The Crayfish Optimization Algorithm (COA) has limitations that affect its optimization performance seriously. The competition stage of the COA uses a simplified mathematical model that concentrates on relations of distance between crayfish only. It is deprived of a stochastic variable and is not abl...

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<i>Background</i>: The Multi Depot Pickup and Delivery Problem with Time Windows and Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing problem with many real-world constraints. Due to its complexity, solution approaches with sufficiently good quality ide...

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Driven by the urgent demand for low-frequency vibration and noise control in engineering scenarios such as automobiles, acoustic metamaterials (AMs), as a new class of functional materials, have demonstrated significant application potential. This paper proposes a low-frequency band gap optimization...

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The Gaining–Sharing Knowledge-based (GSK) algorithm is a human-inspired metaheuristic that models how people learn and disseminate knowledge across their lifetime. It has shown promising results across a range of engineering optimization problems. However, one of its major limitations lies in the us...

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A continuous orthogonal moment is chosen as an image feature descriptor, and a rotation correction algorithm is proposed that can accommodate any order and repetition. In order to demonstrate the expanded application scope of the algorithm, a color image watermarking algorithm based on quantization...

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IntroductionFrequency oscillations induced by stochastic disturbances pose significant challenges to grid-connected photovoltaic (PV) systems. This study proposes an adaptive optimization strategy for photovoltaic-energy storage systems (PV-ESS) based on a GA-BP neural network to address this issue....

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The variation process of anchor bolt (cable) stress exhibits distinct short-term fluctuations and long-term temporal dependencies. However, traditional single prediction models have limited capability in modeling long-term trends and insufficient sensitivity to local fluctuations, often making it di...

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Differential equations are equations that relate a function to one or more of its derivatives. Nonlinear means that the equation is not directly proportional to the function and its derivatives. In other words, its variables cannot be separated simply. The dependent variable and its derivatives are...

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Within computer-aided geometric design (CAGD), Said–Ball curves are primarily adopted in domains such as 3D object skeleton modeling, vascular structure repair, and path planning, owing to their flexible geometric properties. Techniques for curve degree reduction seek to reduce computational and sto...

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This research aims to develop a new transfer function to transform continuous space to binary space using the Polar Lights Optimizer (PLO) algorithm for the feature selection problem. The PLO algorithm relies on simulating the behaviour of the aurora borealis to achieve a balance in exploring and e...

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