Study on the evolutionary mechanisms driving deformation damage of dry tailing stack earth–rock dam under short-term extreme rainfall conditions

Natural Hazards, Journal Year: 2023, Volume and Issue: 119(3), P. 1913 - 1939

Published: Sept. 21, 2023

Language: Английский

---

Application of artificial intelligence in coal mine ultra-deep roadway engineering—a review

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(10)

Published: Aug. 19, 2024

The deep integration of computer field and coal mining is the only way to mine intellectualization. A variety artificial intelligence tools have been applied in open-pit shallow mines. However, with geometric increase demand, contradiction between supply demand becoming more serious, exploitation resources from layer (> 600 m) has become an inevitable trend. Well then, as a new engineering scene, harsh conditions "three high one disturbance" seriously threaten safety personnel. superposition complex environment makes number input factors sharply, which leads application roadway engineering. guidance not mature, construction various databases missing, there are still some problems universality applicability. To this end, paper starts introduction operating characteristics tools, conducts comprehensive study relevant high-level articles published top journals. It systematically sorts out research progress that successfully solved five directions rock mechanics strength, surrounding stability, rock-burst, roof fall risks micro-seismic events. While objectively evaluating performance different it also expounds its own views on key results. Literature review shows whether development tool or comparative model, ANN than 98%, performs extremely well direction stability risk, accuracy rate 90%. As most mature AI application, mechanical strength experienced process "SVM → DL XGBoost RF". dataset small samples (< 100) big 1000), R2 tree-based models can be stabilized at 95%. rock-burst prediction mainly focuses monitoring data. Whether sample large-scale data BN remains above 85%. evaluation events recent years. image processing CNN important. signal recognition classification accounts for 90%, potential source location needs further explored. In general, nature itself first choice almost all influencing factors. At same time, update iteration methods (micro-seismic, ground sound, separation, deformation, etc.) expands database, making possible obtain due threat life cost equipment, very difficult before. parameter selection method combining lithology conditions, geological will gradually research. Finally, follow-up work collation on-the-spot investigation, existing mines, explores engineering, puts forward focus challenging future, gives opinions.

Language: Английский

---

Investigating the Slurry Fluidity and Strength Characteristics of Cemented Backfill and Strength Prediction Models by Developing Hybrid GA-SVR and PSO-SVR

Mining Metallurgy & Exploration, Journal Year: 2022, Volume and Issue: 39(2), P. 433 - 452

Published: Feb. 3, 2022

Language: Английский

---

Hybridizing five neural-metaheuristic paradigms to predict the pillar stress in bord and pillar method

Frontiers in Public Health, Journal Year: 2023, Volume and Issue: 11

Published: Jan. 24, 2023

Pillar stability is an important condition for safe work in room-and-pillar mines. The instability of pillars will lead to large-scale collapse hazards, and the accurate estimation induced stresses at different positions pillar helpful design guaranteeing stability. There are many modeling methods evaluate their stability, including empirical numerical method. However, difficult be applied places other than original environmental characteristics, often simplify boundary conditions material properties, which cannot guarantee design. Currently, machine learning (ML) algorithms have been successfully assessment with higher accuracy. Thus, study adopted a back-propagation neural network (BPNN) five elements sparrow search algorithm (SSA), gray wolf optimizer (GWO), butterfly optimization (BOA), tunicate swarm (TSA), multi-verse (MVO). Combining metaheuristic algorithms, hybrid models were developed predict stress within pillar. weight threshold BPNN model optimized by mean absolute error (MAE) utilized as fitness function. A database containing 149 data samples was established, where input variables angle goafline (A), depth working coal seam (H), specific gravity (G), distance point from center (C), (D), output variable stress. Furthermore, predictive performance proposed evaluated metrics, namely coefficient determination (R 2 ), root squared (RMSE), variance accounted (VAF), (MAE), percentage (MAPE). results showed that good prediction performance, especially GWO-BPNN performed best (Training set: R = 0.9991, RMSE 0.1535, VAF 99.91, MAE 0.0884, MAPE 0.6107; Test 0.9983, 0.1783, 99.83, 0.1230, 0.9253).

Language: Английский

---

Implementation of Adaptive Neuro-Fuzzy Inference System and Image Processing for Design Applications Paper Age Prediction

Jurnal Riset Ilmu Teknik, Journal Year: 2023, Volume and Issue: 1(1), P. 45 - 57

Published: May 31, 2023

The development of technology today is widely misused by some people who intend to forge paper on documents and books. One way find out the authenticity a knowing its age. age can be known in several ways: carbon dating, uranium potassium-argon dating. But these methods still have weaknesses, requiring sophisticated equipment at high cost, long processes get results limited access. To solve this problem, researchers made an application that identify range sheet with faster process, low cost does not used laboratory employees alone. Paper Age Prediction Application desktop-based, using MATLAB programming language Anfis Sugeno (TSK) Gaussian membership function method. Image processing taking average values C, M, Y, K from 70 images as database will trained ANFIS. research method uses interviews, observations, literature studies—the prototype test showed success rate identifying 60 data had been 100% against 40 42.5%.

Language: Английский

---