Efficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results ...

As the number of monitored individuals rises and multipath effects disrupt signals, existing queue monitoring solutions fail to meet efficiency needs. This paper proposes a passive line-of-sight (LOS) human queue detection method based on channel ...

The gas insulated transmission line (GIL), a crucial component of the power system, faces challenges in mechanical fault diagnosis including difficulties in quantifying sensor signal selection, balancing recognition accuracy, and model training ...

• Trajectory planning with integrating human skill.
• Manual skill imitation with adaptive via-point and hyperparameter.
• A motion capture system for capturing manual teaching trajectory data.
• Fruit flexible collecting trajectory ...

The flexible collection is vital for the intelligent grape-picking robot. In view of the reliable operation method obtained by long-term training of human prior skill, a fruit flexible collecting trajectory planning method based on manual skill ...

Reliability-based design optimization (RBDO) integrates various uncertainties into the design optimization process, offering a more realistic and robust approach compared to traditional deterministic design optimization methods. Thus, RBDO has ...

In this paper, a new switching sequence convex optimization (SSCO) algorithm is proposed for solving non-convex optimization problem with complex time-varying relaxation matrix structures that arises during output feedback design. Firstly, the ...

The paper aims to solve the problem of multi-agent path planning in complex environment using optimization algorithm. To address the issue of local optimum and premature convergence, a new method is proposed based on the whale optimization ...

The Heap-Based Optimization (HBO), a novel meta-heuristic algorithm, constructs a hierarchical heap resembling a company structure to facilitate interaction among search agents. This enables the search agent to learn various levels of information ...

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• Proposed a novel Heap-based optimizer based on reinforcement learning.
• It is proposed to control the search scope of the search agent through reinforcement learning to achieve balanced exploitation and exploration.
• A self-learning ...

The accuracy of solar cell models is crucial for enhancing the performance of solar photovoltaic (PV) systems. However, existing solar cell models lack precise parameters, and the manufacturer's datasheet does not provide the required information ...

Due to the increased integration of distributed generation (DG) in electric power systems, optimal coordination of overcurrent relays has become a key problem in power distribution systems. However, there is a lack of expertise in the creation of ...

• The shear strength of corroded RC beams is predicted using ML approach;
• Experimental data and Gradient Boosting (GB) as ML algorithm are utilized;
• GB model is optimized with 3 hybrid algorithms, in which HGS is the best;
• The ...

Shear strength (SS) is an essential component in the design of reinforced concrete structural elements, particularly in severe settings where reinforcements can occur and cause a loss in SS. The purpose of this work is to develop a framework for ...

Cross-modal hashing has gained popularity in similarity search due to its excellent query efficiency and economical storage costs. However, current models frequently overlook the distinctive property of each modality, resulting in reduced ...

• The proposed IMADS jointly captures specific and shared features of input instances.
• An asymmetric dual supervision learning framework yields effective hash functions.
• A discrete optimization algorithm alleviates cumulative ...

To address the limitations of agricultural UAV in performing trajectory planning in complex hilly terrain, a trajectory planning model based on hilly characteristic terrain and agricultural scheduling requirements is proposed. For obtaining an ...

• A novel IIE-GWO algorithm for UAV trajectory planning problem in complex hilly terrain.
• An interference enhancement model is proposed to improve trajectory search accuracy.
• Fusing Nonlinear Weights and Gaussian Perturbations to ...

Classification of brain signals for character recognition is a challenging task associated with uncertainties. This study aims to present an Improved Type-2 Fuzzy Deep Learning (IT2FDL) framework for uncertainty management in character ...

• An Improved Type-2 Fuzzy Deep Learning (IT2FDL) framework is proposed for uncertainty management in character recognition.
• The Evolutionary Algorithms were employed for this study's optimum design of the proposed IT2FDL.
• Using ...

Compared to wheeled and tracked robots, hexapod robots have higher adaptability and higher flexibility in complex terrains. With various gaits, hexapod robots can fulfill different needs better. Existing researches mainly focused on three common ...

Unmanned Aerial Vehicle (UAV) carries relief materials to perform cooperative delivery mission, which has a high guarantee in both flexibility and security, and can avoid the personal safety threat of pilots in the original delivery mode in the post-...

Nature- and society-inspired metaheuristic algorithms have recently become the most promising technological model. To solve more complex optimization problems and complicated engineering applications, this paper proposes a new people duality ...

Quantitative trading, relying on diverse parameter combinations, is becoming increasingly the norm for trading strategies in financial investments. The performance of these strategies is intricately linked to these parameters. However, the ...

The security of an application is critical for its success, as breaches cause loss for organizations and individuals. Search-based software security testing (SBSST) is the field that utilizes metaheuristics to generate test cases for the software ...

The photovoltaic system has been widely integrated into electrical power grids to produce clean and sustainable energy sources. Precisely modeling of PV systems is crucial to simulate and asset the performance of such power system. Modeling of PV ...