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The deformation of open-pit mine slopes is influenced by various factors such as geological structure, hydrogeological conditions, mining activities, etc., making the prediction model complex. It is difficult to accurately capture all influencing factors. At present, a large number of monitoring devices are deployed around the slope of open-pit mines to record real-time displacement data of open-pit mine slopes. The data has the features of high-dimensional, temporal correlation, and nonlinear. Traditional slope stability analysis methods cannot effectively predict slope deformation without knowing other conditions and only data, it is necessary to use a data-based model to predict the displacement data of open-pit mine slopes in advance for slope stability analysis. In order to solve the above problems, a deformation prediction model for open-pit mine slopes based on the golden jackal optimized multilayer perception machine (GJO-MLP) is proposed. Each agent in GJO is independent of each other and can accelerate the training process of optimizing MLP through parallel computing. GJO can combine the nonlinear modeling and feature extraction capabilities of MLP, making the optimized MLP more advantageous in dealing with complex problems. To test the feasibility and effectiveness of GJO-MLP, GJO-MLP is compared and analyzed with ant colony algorithm optimization based MLP (ACO-MLP), gravity search algorithm optimization based MLP (GSA-MLP), and differential evolution algorithm optimization based MLP (DE-MLP). The simulation results on six datasets show that under the same experimental conditions, GJO-MLP shows better optimization performance compared to the other three algorithms. The slope deformation prediction model based on GJO-MLP is applied to the slope deformation prediction of Baorixile open-pit mine and Huapingzi slope deformation prediction. The results show that under the same conditions, compared to the other three algorithms, the slope deformation prediction model based on GJO-MLP not only show better predictive performance in predicting slope deformation data, but also has better feasibility and robustness.

Combined with the characteristics of open-pit mines in China, the definition of intelligent open-pit mines is given. This paper introduces the overall network architecture, business architecture and collaborative process of the intelligent open-pit mine. The overall network architecture of cloud, edge and end is adopted to realize the collaborative correlation of various production links in the open-pit mine by accessing multi-source heterogeneous data and fully applying advanced technologies such as big data and cloud computing. The business architecture adopts the "5 layers + 3 system" model. The "5 layers" from bottom to top are the basic equipment layer, business data layer, analysis service layer, analysis business layer and analysis presentation layer. And the "3 systems" are data analysis standard system, safety specification standard system, metadata and code specification standard system. The bottom-up collaboration of intelligent open-pit mine should realize "basic + data" support, mine production system collaboration, disaster risk analysis collaboration and business decision-making collaboration. The key technologies such as unmanned technology, digital twin technology, big data collection and analysis technology, risk monitoring and early warning technology of intelligent open-pit mine are discussed. It is pointed out that technologies such as big data and artificial intelligence will become the core driver of open-pit mine intelligence. The platform-based architecture will become the common choice for future intelligent open-pit mine systems.

In order to solve the problem of unmanned truck transportation scheduling in open-pit mines, the minimum sum of fuel cost, fixed start-up cost, breakdown maintenance cost, and network base station construction and maintenance cost are taken as the objective functions. The mining amount of mining station, crushing amount of crushing station, truck number and truck transportation workload are taken as the constraint conditions. The optimization model of unmanned truck transportation scheduling in open-pit mines is established. To solve the problem of imbalance between global exploration and local mining ability in the tunicate swarm algorithm, an improved tunicate swarm algorithm (ITSA) based on Singer mapping and adaptive updating mechanism of parameter position is proposed. And it is applied to solve the optimization model of unmanned truck transportation scheduling in open-pit mines. Singer mapping is introduced to enhance the distribution of the initial tunicate swarm in the solution space and accelerate the compression of the solution space, thus improving the convergence speed of the algorithm. Through the adaptive updating mechanism of parameter position, the positions of the tunicate and the optimal tunicate are adjusted to increase the search range of the solution space. Therefore, the algorithm jumps out of the local optimization. The simulation results show that ITSA has better convergence precision, convergence speed and stability compared with the four population intelligent optimization algorithms of grey wolf optimization algorithm (GWO), whale optimization algorithm (WOA), atom search optimization algorithm (ASO) and tunicate swarm algorithm (TSA). In the unimodal benchmark function, the evaluation indexes of ITSA are far better than those of the other four algorithms, which shows that ITSA has better local mining capacity. In the multi-peak benchmark function, the evaluation indexes of ITSA show better optimization performance, which indicates that ITSA has better global exploration performance. The practical application scenario verification shows that ITSA has faster convergence speed and higher convergence precision when used for solving the unmanned truck transportation scheduling optimization model. And ITSA reduces the truck transportation cost and transportation distance.

In the historical background of "festivalization of culture", to clarify the meaning of festivals is a prerequisite for accomplishing the cultural value of festivals. By interpreting relevant western cultural theories, especially Pieper’s statements, this article argues that "in tune with the world" is the fundamental meaning of festivals. Considered as a result, "in tune with the world" means metaphysical needs are satisfied, and when taken as a prerequisite, "in tune with the world" should rely on totality strength. The enlightenment rationality breaks away from the field of metaphysics due to overemphasis on reflection, which results in the discontinuity of totality strength in the transition from old to new. This is the fundamental reason why some current festivals cannot realize their own values. Therefore, emphasizing a festival’s cultural connotation and exploring the possibility of re-endowing festivals with charm should be the top priority of research on festivals.

The non-axisymmetric problem caused by the fluid sloshing in the tank of a mining concrete mixing tank truck during driving is affected by the excitation of complex road surfaces. The fluid sloshing is coupled with the dynamics of the vehicle body due to the excitation of the complex road surface. The traditional hydraulic drive proportional integral differential (PID) control method is not effective in dealing with such problems, which can easily lead to accidents such as overturning. To improve the accuracy and stability of the hydraulic drive control system, this paper proposes an optimized particle filter PID adaptive control method based on the elastic firefly (FA) algorithm to accelerate the convergence speed of control parameter optimization, and then analyzes its hydraulic drive control characteristics and structural applications, and discusses step steering and double lane change modes are simulated under filling rates of 1.5 and 2.0, respectively. The experimental results show that compared with traditional PID control, the proposed adaptive control method can significantly reduce the average speed error of hydraulic drive control to 0.03km/h and the maximum speed error to 0.17km/h. It also improves the control tracking performance and stability. The practicality of the adaptive hydraulic drive is verified in the filling rate experiments under step steering and double-lane shifting conditions. It has important reference value for the practical application of hydraulic drive control optimization of mining concrete mixing transport tank trucks. [ABSTRACT FROM AUTHOR]

The construction of shiology system is the premise for comprehensively solving the issues of human shiance. The core of the construction of the shiology system is to reveal the inclusion and juxtaposition of relationships within shiance based on a comprehensive understanding of human shiance issues. The shiology system discussed in this paper is a four-level discipline system with the basic structure of shiology triangle composed of eaters' demands, food acquisition and shiance order, and it is currently in the form of "1-3-13-36". From a longitudinal point of view, 53 inclusion relationships are established among disciplines at all levels. Horizontally, 53 juxtapositions are established between disciplines at the same level. The shiology system is bounded by human shiance issues, not involving non-shiance issues areas. Human cognition of shiance and shiance issues must go through three historical stages as fragmented cognition, block-based cognition and holistic cognition. The construction of the shiology system marks that humans have entered the stage of "holistic cognition" of shiance. As the Chinese proverb goes, "food is the paramount necessity of the people". Shiology system interprets its connotation and extension. To solve shiance issues holistically, it need to ensure food security, enable people to eat healthy, and foster an enduring and stable society. And shiology system is a global public product which comprehensively solves shiance issues. [ABSTRACT FROM AUTHOR]

This study presents a numerical investigation of a solitary wave breaking over a slope by using the phase-field lattice Boltzmann method. The incompressible two-phase flow equations are solved by using a velocity-based formulation of the two-phase lattice Boltzmann method with a central-moment collision model to accurately simulate wave breaking problems. For interface capture, a phase-field lattice Boltzmann method that ensures mass conservation is employed. The validity of the proposed method is confirmed through solitary wave propagation and transformation problems, and the obtained results are in good agreement with the experimental and calculated results. The proposed method is then employed to analyze wave breaking on a slope, demonstrating strong concordance with experimental data and existing computational findings. By analyzing the instantaneous flow characteristics and the temporal evolution of the variation in kinetic, potential, and total energy from deep to shallow water, the model can reveal the macroscopic characteristics of solitary wave breaking. Because the phase-field model effectively simulates wave breaking and air entrainment, it can depict wave energy dissipation more accurately than the single-phase lattice Boltzmann method with free surface tracking. [ABSTRACT FROM AUTHOR]