بدائل البحث:
process optimization » model optimization (توسيع البحث)
case optimization » based optimization (توسيع البحث), phase optimization (توسيع البحث), dose optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
based process » based processes (توسيع البحث), based probes (توسيع البحث), based proteins (توسيع البحث)
binary based » linac based (توسيع البحث), binary mask (توسيع البحث)
based case » base case (توسيع البحث), based cancer (توسيع البحث)
process optimization » model optimization (توسيع البحث)
case optimization » based optimization (توسيع البحث), phase optimization (توسيع البحث), dose optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
based process » based processes (توسيع البحث), based probes (توسيع البحث), based proteins (توسيع البحث)
binary based » linac based (توسيع البحث), binary mask (توسيع البحث)
based case » base case (توسيع البحث), based cancer (توسيع البحث)
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41
Layout of hybrid flow shop scheduling.
منشور في 2025"…In recent years, due to the advantages of nonlinear access and fully parallel processing, the probe machine has shown powerful computing capabilities and promising applications in solving various combinatorial optimization problems. …"
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42
Probe combines and as a 2-aggregation.
منشور في 2025"…In recent years, due to the advantages of nonlinear access and fully parallel processing, the probe machine has shown powerful computing capabilities and promising applications in solving various combinatorial optimization problems. …"
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43
Scheduling Gantt chart for instance j10c10c6.
منشور في 2025"…In recent years, due to the advantages of nonlinear access and fully parallel processing, the probe machine has shown powerful computing capabilities and promising applications in solving various combinatorial optimization problems. …"
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44
Scheduling Gantt chart for instance j30c5e10.
منشور في 2025"…In recent years, due to the advantages of nonlinear access and fully parallel processing, the probe machine has shown powerful computing capabilities and promising applications in solving various combinatorial optimization problems. …"
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45
Box plot comparison on instance j30c5e10.
منشور في 2025"…In recent years, due to the advantages of nonlinear access and fully parallel processing, the probe machine has shown powerful computing capabilities and promising applications in solving various combinatorial optimization problems. …"
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46
Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
منشور في 2019"…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …"
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48
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49
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50
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51
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52
Analysis and design of algorithms for the manufacturing process of integrated circuits
منشور في 2023"…From this, we propose: (i) a new ILP model, and (ii) a new solution representation, which, unlike the reference work, guarantees that feasible solutions are obtained throughout the generation of new individuals. Based on this new representation, we proposed and evaluated other approximate methods, including a greedy algorithm and a genetic algorithm that improve the state-of-the-art results for test cases usually used in the literature. …"
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53
Summary of LITNET-2020 dataset.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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54
SHAP analysis for LITNET-2020 dataset.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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55
Comparison of intrusion detection systems.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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56
Parameter setting for CBOA and PSO.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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57
NSL-KDD dataset description.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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58
The architecture of LSTM cell.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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59
The architecture of ILSTM.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"
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60
Parameter setting for LSTM.
منشور في 2023"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"