hancc 2021-04-20 22:32:52
Description: Using particle swarm optimization algorithm to optimize the initial weights and thresholds of BP neural network, the optimization effect is good,
Plat: matlab | Size: 48KB | Downloads: 0
dadadfdafdafd 2021-04-20 18:18:30
Description: EfficientDet network model code for multi-class target detection
Plat: Python | Size: 9783KB | Downloads: 0
leike0429 2021-04-20 15:45:11
Description: Whale optimization Python version of the code, for everyone to download together to learn.
Plat: Python | Size: 2KB | Downloads: 0
NOBOCY 2021-04-19 21:46:11
Description: The matlab code of the gray prediction model GM(1,1) used for life prediction
Plat: matlab | Size: 1KB | Downloads: 0
到处看看一看 2021-04-19 21:34:00
Description: Particle Swarm Optimization (Pso) is an evolutionary computing technique, which is derived from the study of the predatory behavior of birds. The basic idea of particle swarm optimization algorithm is to find the optimal solution through the cooperation and information sharing among the individuals in the group
Plat: matlab | Size: 42KB | Downloads: 0
ShangShangHappy 2021-04-19 17:34:05
Description: python implement PSO algorithm
Plat: Python | Size: 100KB | Downloads: 0
yuluotianhan、 2021-04-19 17:20:18
Description: Information about genetic algorithm, can explain genetic algorithm very clearly
Plat: matlab | Size: 3859KB | Downloads: 0
进修 2021-04-18 18:48:55
Description: Wince5 multifunctional unit converter
Plat: MQL | Size: 153KB | Downloads: 0
weic1 2021-04-18 14:51:29
Description: Artificial intelligence, neural network, deep learning: for point classification
Plat: Python | Size: 2KB | Downloads: 0
当当lei叮叮 2021-04-18 13:53:39
Description: What is fitting?You have a bunch of data points, I have a function, but a lot of the parameters of the function are unknown, all I know is that your data points are on my function, so I can use your data points to find the unknown parameters of my function.
Plat: Python | Size: 2981KB | Downloads: 0
shuxuejianmo 2021-04-18 02:26:12
Description: Mathematical modeling data need to take the subsequent upload code
Plat: Python | Size: 7572KB | Downloads: 0
yytyj 2021-04-17 21:57:17
Description: Using C + +, framework using QT, to achieve the reservoir numerical simulation function, the corresponding calculation, resources from GitHub
Plat: C/C++ | Size: 9243KB | Downloads: 0
yytyj 2021-04-17 21:47:48
Description: Is written in C + +, the use of the framework is QT, online hotel management system
Plat: C/C++ | Size: 10723KB | Downloads: 0
鱼逸 2021-04-17 02:50:58
Description: Four point interpolation function
Plat: matlab | Size: 1KB | Downloads: 0
聆听i 2021-04-16 12:05:36
Description: The residual network model was used to classify the data
Plat: Python | Size: 5144KB | Downloads: 2
hu123hu 2021-04-16 08:38:37
Description: Matlab code of best neighbor guided artificial bee colony algorithm (NABC)
Plat: matlab | Size: 1KB | Downloads: 0
hu123hu 2021-04-15 16:44:15
Description: Matlab code of Multi-strategy brain storm optimization algorithm with dynamic parameters adjustment (MSBSO)
Plat: matlab | Size: 4695KB | Downloads: 5
hu123hu 2021-04-15 16:41:56
Description: Matlab code of Multi-strategy serial cuckoo search algorithm for global optimization (MSSCS)
Plat: matlab | Size: 1781KB | Downloads: 0
hu123hu 2021-04-15 14:23:19
Description: Matlab code of Enhancing differential evolution with random neighbors based strategy (RNDE)
Plat: matlab | Size: 2KB | Downloads: 1
hu123hu 2021-04-15 14:20:40
Description: Matlab code of Enhancing firefly algorithm with courtship learning (FA-CL)
Plat: matlab | Size: 1780KB | Downloads: 0
NainSale97 2021-04-15 03:42:57
Description: The channel encoder introduces controlled redundancy in such a way that if an error occurs in the communications channel it can be detected and / or corrected. There are different error protection systems: block codes, convolutional codes, trellis codes, etc. In this practice we are going to focus on the simplest: linear block codes
Plat: matlab | Size: 1116KB | Downloads: 0
songhaoyuan 2021-04-14 23:27:24
Description: Over the past two decades Machine Learning has become one of the mainstays of information technology and with that, a rather central, albeit usually hidden, part of our life. With the ever increasing amounts of data becoming available there is good reason to believe that smart data analysis will become even more pervasive as a necessary ingredient for technological progress.
Plat: Python | Size: 8279KB | Downloads: 0
cycycycyc 2021-04-14 19:26:38
Description: Classical cluster method based on block diagonal. Spectrum clustering visualization algorithm, very detailed description.
Plat: matlab | Size: 4KB | Downloads: 0
markby 2021-04-14 10:40:24
Description: AFM recommendation algorithm prepared with Python language, there are detailed description
Plat: Python | Size: 1KB | Downloads: 0
markby 2021-04-14 10:37:35
Description: AutoInt recommendation algorithm prepared with Python language, there are detailed description.
Plat: Python | Size: 2KB | Downloads: 0
markby 2021-04-14 10:35:50
Description: DCN recommended algorithm prepared with Python language, there are detailed description.
Plat: Python | Size: 615KB | Downloads: 1
markby 2021-04-14 10:34:39
Description: The DeepFM recommendation algorithm written in Python language is described in detail.
Plat: Python | Size: 745KB | Downloads: 0
markby 2021-04-14 10:33:11
Description: Use Python language FM recommendation algorithm, have detailed description.
Plat: Python | Size: 556KB | Downloads: 0
马荥利 2021-04-13 18:33:11
Description: By changing different parameters, we can get the peak search
Plat: matlab | Size: 3KB | Downloads: 0
高进2021 2021-04-13 14:14:58
Description: The description and detection of local image features can help to identify objects. SIFT features are based on some local appearance points of interest on the object, independent of the size and rotation of the image. The tolerance of light, noise and micro angle change is also quite high. Based on these characteristics, they are highly significant and relatively easy to extract. In a large number of feature databases, it is easy to identify objects, and there are few misidentifications. The detection rate of partial object occlusion using SIFT feature description is also quite high, even more than three sift object features are enough to calculate the position and orientation. Under the current computer hardware speed and the condition of small feature database, the identification speed can be close to real-time operation. SIFT features have a large amount of information and are suitable for fast and accurate matching in massive databases.
Plat: Python | Size: 5KB | Downloads: 0
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