Objective: Pulmonary function parameters play a pivotal role in the assessment of respiratory diseases. However, the accuracy of the existing methods for the prediction of pulmonary function parameters is low. This study proposes a combination algori...
Recently, a population-based intelligent optimization algorithm research has been combined with multiple algorithms or algorithm components in order to improve the performance and robustness of an optimization algorithm. This paper introduces the ide...
Agriculture’s sustainable growth necessitates the application of advanced science and technology to ensure the sensible use of resources and improve the agricultural economy’s long-term stability. In this study, apple trees were employed...
The division of the flood season is of great significance for the precise operation of water conservancy projects, flood control and disaster reduction, and the rational allocation of water resources, alleviating the contradiction of the uneven spati...
he accurate forecasting of carbon dioxide (CO2) emissions from fossil fuel energy consumption is a key requirement for making energy policy and environmental strategy. In this paper, a novel quantum harmony search (QHS) algorithm-based discounted mea...
Accurate power generation forecasting provides the basis of decision making for electric power industry development plans, energy conservation and environmental protection. Since the power generation time series are rarely purely linear or nonlinear,...
In mechanism design with symmetrical or asymmetrical motions, obtaining high precision of the input path given by working requirements of mechanisms can be a challenge for dimensional optimization. This study proposed a novel hybrid-combined differen...
The triple-frequency linear combination method can provide combinations with different characteristics and is one of the important methods to improve the performance of navigation services. Due to the large number of combinations and different combin...
Combining multiple biomarkers to provide predictive models with a greater discriminatory ability is a discipline that has received attention in recent years. Choosing the probability threshold that corresponds to the highest combined marker accuracy...
Drug combinatorial therapy is a promising strategy for combating complex diseases due to its fewer side effects, lower toxicity and better efficacy. However, it is not feasible to determine all the effective drug combinations in the vast space of pos...
Combined heat and power (CHP) plants are known as efficient technologies to reduce environmental emissions, balance energy costs, and increase total energy efficiency. To obtain a more efficient system, various optimization methods have been employed...
This paper presents a computationally efficient novel heuristic approach for solving the combined heat and power economic dispatch (CHP-ED) problem in residential buildings considering component interconnections. The proposed solution is meant as a s...
The Artificial Hummingbird Algorithm (AHA) is a recent swarm intelligence optimizer with a simple structure and few control parameters. However, it still faces limitations in search regulation, population diversity maintenance, and late-stage exploit...
The differential evolution (DE) algorithm is a popular and efficient evolutionary algorithm that can be used for single objective real-parameter optimization. Its performance is greatly affected by its parameters. Generally, parameter control strateg...
This paper proposes a hybrid algorithm that combines two prominent nature-inspired meta-heuristic strategies to solve the combined heat and power (CHP) economic dispatch. In this line, an innovative hybrid heap-based and jellyfish search algorithm (H...
The optimal scheduling of multi-type combine harvesters is a crucial topic in improving the operating efficiency of combine harvesters. Due to the NP-hard property of this problem, developing appropriate optimization approaches is an intractable task...
Exchange rate forecasting is a crucial but challenging task due to the uncertainty and fuzziness of the associated data caused by complex influence factors. However, most traditional forecasting methods ignore the ambiguity of the data itself. Thus,...
Given the growing number of development projects, proper project planning and management are crucial. The purpose of this paper is to introduce a heuristic algorithm for scheduling a power plant project construction and project resource management to...
Intelligent control algorithms are essential for enhancing combine harvester efficiency and minimizing losses, especially as global food demand rises and labor shortages become more severe. This paper provides a comprehensive overview of the evolutio...
Due to the inflexibility of cogeneration power plants and the uncertainty of wind power production, the excess power of the distribution network brings challenges to the power grid operation. This paper introduced an improved moth-flame optimization...
The combination of adaptive filters is an effective approach to improve filtering performance. In this paper, we investigate the performance of an adaptive combined scheme between two adaptive multiple-input single-output (MISO) filters, which can be...
The aim of electrical load dispatch (ELD) is to achieve the optimal planning of different power plants to supply the required power at the minimum operation cost. Using the combined heat and power (CHP) units in modern power systems, increases energy...
To address the shortcomings of poor convergence and the ease of falling into local optima when using the traditional gold rush optimization (GRO) algorithm to solve the complex scheduling problem of a combined cooling, heating, and power (CCHP) micro...
With the development of the advanced Intelligent Transportation System (ITS) in modern cities, it is of great significance to upgrade the forecasting methods for travel demand with the impact of ITS. The widespread use of ITS clearly changes the urba...
It is well accepted that combined heat and power (CHP) generation can increase the efficiency of power and heat generation at the same time. With the increasing penetration of CHPs, determination of economic dispatch of power and heat becomes more co...
The reasonable and efficient use of the abundant biomass resources in rural areas has not been realized. Therefore, the concept of a combined cooling, heating, and power (CCHP) microgrid system, considering biomass pyrolysis and gasification, has bee...
The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-pre...
An image semantic segmentation algorithm using fully convolutional network (FCN) integrated with the recently proposed simple linear iterative clustering (SLIC) that is based on boundary term (BSLIC) is developed. To improve the segmentation accuracy...
Wind speed forecasting plays a key role in wind-related engineering studies and is important in the management of wind farms. Current forecasting models based on different optimization algorithms can be adapted to various wind speed time series data....
With increasing attention to sustainability and energy efficiency in transportation systems, advanced intelligent algorithms provide promising solutions for optimizing urban rail transit operations. This study addresses the challenge of optimizing tr...
This paper addresses the machining requirements for large aerospace structural components using robotic systems and proposes a method for rapid workpiece positioning that combines the simplicity of vision-based positioning with the precision of conta...
In this paper a genetic algorithm (GA) approach to design of multi-layer perceptron (MLP) for combined cycle power plant power output estimation is presented. Dataset used in this research is a part of publicly available UCI Machine Learning Reposito...
In an effort to address the load adjustment time in the thermal and electrical load distribution of thermal power plant units, we propose an optimal load distribution method based on load prediction among multiple units in thermal power plants. The p...
In this paper, a combined structure of algorithms based on field-oriented control (FOC) and direct torque control (DTC) is proposed for improving the performance of a three-phase induction motor (IM) over a wide range of torque loads. The objective o...
In this paper, to further improve the filtering performance and enhance the poor tracking capability of the conventional combined step-size affine projection sign algorithm (CSS-APSA) in system identification, we propose a simplified CSS-APSA (SCSS-A...
To address the challenge of monitoring BeiDou RDSS signals under low signal-to-noise ratio (SNR) and high-dynamic conditions, this paper introduces a hierarchical joint processing algorithm combining PMF-FFT and PMF-FRFT. The method counters the ener...
This paper presents the optimization of fuel cost, emission of NOX, COX, and SOX gases caused by the generators in a thermal power plant using penalty factor approach. Practical constraints such as generator limits and power balance were considered....
Autonomous driving solutions for agricultural machinery have advanced rapidly; however, large-wheeled harvesters present unique challenges compared to traditional vehicles. Specifically, the 5.4 m cutting width, 9.2 m minimum turning diameter, and re...
The multi-source data collected by the power Internet of Things (IoT) provide the data foundation for the power big data analysis. Due to the limited computational capability and large amount of data collection terminals in power IoT, the traditional...
The frequent fluctuation of pork prices has seriously affected the sustainable development of the pork industry. The accurate prediction of pork prices can not only help pork practitioners make scientific decisions but also help them to avoid market...
Accurate wind power forecasting helps relieve the regulation pressure of a power system, which is of great significance to the power system’s operation. However, achieving satisfactory results in wind power forecasting is highly challenging due...
The deep carbonate reservoirs in the Yingzhong Block of the Qaidam Basin exhibit strong vertical heterogeneity and complex natural fracture development. Conventional fracability evaluation methods struggle to accurately characterize formation feature...
Underwater acoustic channels often have to face the interference of impulsive noise, which is usually modeled by α-stable distribution in simulation experiments. To solve the problem of underwater acoustic channel estimation under impulsive noi...
Active headrest can reduce the low-frequency noise around ears based on the principle of active noise control. This paper presents a combination of robust algorithm and head-tracking for a feedforward active headrest to reduce the broadband noise for...
The ItemCF algorithm is currently the most widely used recommendation algorithm in commercial applications. In the early days of recommender systems, most recommendation algorithms were run on a single machine rather than in parallel. This approach,...
Indirect detection phase control algorithms, such as the dithering algorithm and the stochastic parallel gradient descent algorithm (SPGD), have simple system structures and are applicable to filled-aperture coherent combinations with high efficiency...
Distributed energy resources provide local power as a supplement on the customer side. Recent rapid development of the distributed energy source enhances the clear energy production at the terminal of the power system. Whereas the small capacity of a...
For most of differential evolution (DE) algorithm variants, premature convergence is still challenging. The main reason is that the exploration and exploitation are highly coupled in the existing works. To address this problem, we present a novel DE...
Dental panoramic radiography (DPR) is a method commonly used in dentistry for patient diagnosis. This study presents a new technique that combines a regional convolutional neural network (RCNN), Single Shot Multibox Detector, and heuristic methods to...
Conventional adaptive beamforming algorithms often suffer from significant performance degradation when steering vector mismatches and covariance matrix estimation errors occur. To address this problem, this paper proposes an adaptive robust beamform...
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