Data_Sheet_1_Ecologically and biophysically optimal allocation of expanded soy production in Bavaria, Germany.docx by Swantje Gebhardt (13258488)

Minimal data set definition. by Hui Yang (91136)

Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

Plan frame of the house. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Ablation test results. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Hyperparameter selection test. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Multiple index test results of different methods. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Backtracking strategy diagram. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Comparison of differences in literature methods. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

New building interior space layout model flow. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Schematic of iteration process of IDE-IIGA. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Schematic diagram of IGA chromosome coding. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Example of R code with data for calculations. by Panayiotis D. Ziakas (9510346)

“…We obtained multiple consecutive samples using the same terms to validate against sampling bias. We consolidated national-level incident cases and deaths weekly and transformed them to a range between 0 to 100 through the min-max normalization algorithm. …”

Performance comparison of different methods. by Hui Zhao (7395)

“…Existing solutions, such as traditional interference suppression techniques that rely on static spectrum allocation and fixed interference patterns, are no longer able to adapt to the rapidly changing electromagnetic environment and face computational complexity challenges when processing large amounts of real-time data. This study proposes an intelligent anti-interference algorithm that combines deep neural networks and game theory, and constructs a model based on near-end strategy optimization. …”

Comparative analysis of existing methods. by Hui Zhao (7395)

“…Existing solutions, such as traditional interference suppression techniques that rely on static spectrum allocation and fixed interference patterns, are no longer able to adapt to the rapidly changing electromagnetic environment and face computational complexity challenges when processing large amounts of real-time data. This study proposes an intelligent anti-interference algorithm that combines deep neural networks and game theory, and constructs a model based on near-end strategy optimization. …”

BER at different SNR levels. by Hui Zhao (7395)

“…Existing solutions, such as traditional interference suppression techniques that rely on static spectrum allocation and fixed interference patterns, are no longer able to adapt to the rapidly changing electromagnetic environment and face computational complexity challenges when processing large amounts of real-time data. This study proposes an intelligent anti-interference algorithm that combines deep neural networks and game theory, and constructs a model based on near-end strategy optimization. …”

The classification method of the alliance game. by Hui Zhao (7395)

“…Existing solutions, such as traditional interference suppression techniques that rely on static spectrum allocation and fixed interference patterns, are no longer able to adapt to the rapidly changing electromagnetic environment and face computational complexity challenges when processing large amounts of real-time data. This study proposes an intelligent anti-interference algorithm that combines deep neural networks and game theory, and constructs a model based on near-end strategy optimization. …”

Box of the NSO. by Hui Zhao (7395)

“…Existing solutions, such as traditional interference suppression techniques that rely on static spectrum allocation and fixed interference patterns, are no longer able to adapt to the rapidly changing electromagnetic environment and face computational complexity challenges when processing large amounts of real-time data. This study proposes an intelligent anti-interference algorithm that combines deep neural networks and game theory, and constructs a model based on near-end strategy optimization. …”

Decision model based on the NSO. by Hui Zhao (7395)

“…Existing solutions, such as traditional interference suppression techniques that rely on static spectrum allocation and fixed interference patterns, are no longer able to adapt to the rapidly changing electromagnetic environment and face computational complexity challenges when processing large amounts of real-time data. This study proposes an intelligent anti-interference algorithm that combines deep neural networks and game theory, and constructs a model based on near-end strategy optimization. …”

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”