jason getter

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PSO: Using PSO algorithm to optimize two-element function to find optimal individual fitness-jason NIU

Figure[x,y] = Meshgrid ( -5:0.1:5,-5:0.1:5), z = x.^2 + y.^2-10*cos (2*pi*x)-10*cos (2*pi*y) + 20;mesh (x, y, z) hold onc1 = 1.49445;C2 = 1.49445;maxgen = 1000; Sizepop = 100; Vmax = 1; Vmin = -1;popmax = 5; Popmin = -5;for i = 1:sizepop pop (i,:) = 5*rands); V (i,:) = Rands); Fitness (i) = Fun (Pop (i,:)); end[bestfitness Bestindex] = max (fitness); zbest = Pop (bestindex,:); Gbest = Pop; Fitnessgbest = fitness; Fitnesszbest = bestfitness; For i = 1:maxgen for j = 1

Interview with Jason Weisser: SOA is very difficult and important

In the interview, Mr. Jason Weisser, vice president of IBM software enterprise integrated solutions and one of the founding SOA experts, gave a detailed answer to some of the main questions about SoA. SOA is not a product Question: Tell me directly what SOA is? Jason Weisser: Well, I will tell you what SOA is. SOA is not a "thing", a product, or a software suite that can be placed on a CD. You cannot pick

Android Gsonformat Plugin parsing jason Data + Wind Weather Interface analysis case

/src/com/litesuits/http/dataPart II: Using Gsonformat to parse and wind weather interface data Wind Weather: http://www.heweather.com/ 3,000 visits per day, enough for our amateurs, to make a weather forecast demo is good. First is the weather data obtained from wind weather, Jason format, put on jason.parse.online.fr to see this: but!!!!! According to the first part of the method, a Jason data copied

Python3 Jason, Pickle and Cpickle

Python JSONJSON (JavaScript Object Notation) is a lightweight data interchange format that is easy for people to read and write. The JSON data format is actually the dictionary format in Python, which can contain arrays enclosed in square brackets, which is the list in Python.In Python, there are modules--jason and pickle that specialize in the Jason format.The Jason

SA: Using SA algorithm to solve TSP (data is the horizontal ordinate of 14 virtual cities) problem--jason Niu

%SA: Using SA algorithm to solve TSP (data is a horizontal ordinate of 14 virtual cities)--jason niu X = [16.4700 96.1000 16.4700 94.4400 20.0900 92.5400 22.39 00 93.3700 25.2300 97.2400 22.0000 96.0500 20.4700 97.0200 17.2000 96.2900 16.3000 97.3800 14.0500 98.1200 16.5300 97.3800 21.5200 95.5900 19.4100 97.1300 20.0900 92.5500];D = Distan CE (X); N = size (d,1); T0 = 1e10; Tend = 1e-30; L = 2; Q = 0.9; Time = Ceil (double (

The ae:ae of TF realizes the real value comparison of the TF self-brought data set compared with AE first encoder the accurate comparison of decoder predictive numbers-jason NIU

()) total_batch = Int (mnist.train.num_examples/batch_size) # Training Cycle For epoch in range (Training_epochs): # Loop through all batches for I in Range (Total_batch): BATC H_xs, Batch_ys = Mnist.train.next_batch (batch_size) # max (x) = 1, min (x) = 0 # Run optimization op (backprop) and cost op (to get loss value) _, c = Sess.run ([Optimizer, Cost], feed_dict={x:batch_xs}) # Display lo GS per epoch step if epoch% Display_step = = 0:print ("Epoch:", '%04d '% (epoch+1), "Co St= "," {:. 9

Realize handwritten numeral recognition (data set 50000 pictures) Compare 3 kinds of algorithm neural network, gray average value, SVM respective accuracy rate-jason NIU

50000 pictures of the handwritten data set 0~9 recognition of Arabic numerals, and the accuracy of the analysis of the results,Handwritten digital data set download: http://yann.lecun.com/exdb/mnist/First of all, using the properties of the picture itself, the image of the gray average to identify the classification, I run out of the accuracy rate is about 22%Using the gray average of images to classify and realize handwritten image recognition (DataSet 50000 photos)--

[ios+php Jason format for sending and parsing]

Server-side PHP file connect.php:PHP$q=mysql_connect("localhost", "root", "" "); if(!$q) { die(' Could not connect: '.Mysql_error()); } mysql_query("Set names UTF8");//reading data with UTF8 mysql_select_db("Jasontest",$q);//Database $sql= "SELECT * from UserInfo"; $query=mysql_query($sql); while($row=Mysql_fetch_array($query)){ $com=$row; } EchoJson_encode ($com);?>iOS segment parsing:-(Ibaction) Clickbutton: (IDSender {[Nsthread detachnewthreadselector

Jackson-Build Jason Tool-simple example

Home:http://jackson.codehaus.org/Https://github.com/FasterXML/jacksonCurrently Jackson is divided into three parts that need to be downloaded separately;Jackson-annotations-2.5.0.jar,jackson-core-2.5.0.jar,jackson-databind-2.5.0.jarJava Bean: PackageCom.srie.test.json;Importjava.io.IOException;ImportCom.fasterxml.jackson.databind.ObjectMapper; Public classTestjson { Public Static voidMain (string[] args)throwsIOException {User user1=NewUser (1, "a"); User User2=NewUser (2, "B"); Objectmapper Map

FZU2164 Jason ' s problem

The topic is very understood, test instructions is for you n! and the K-suffix zero, allowing you to find the number of binary B that fits the criteria.Suppose you've already asked for a n! decomposition, and then explained the first set of examples. n=10,k=2,n! The factorial can be expressed as 2^8*3^4*5^2*7, and then converted into this form (2^4*3^2*5) ^2*7, you can know how many kinds of feed to meet the conditions, that is, the combination of 2^4*3^2*5, there are 5*3*2 species, which must n

Spring MVC3 annotations @responsebody automatically return to Jason

The third annotation using spring MVC3 @responsebodyFor example:[Java]View PlainCopyprint? @ResponseBody @RequestMapping ("/list") Public list String hql = "Select C from clothing C"; pagenew page Page.setpagesize (6); page = clothingserviceimpl.queryforpagebyhql (page, HQL); return Page.getresult (); } You can then return the JSON using the spring MVC default configuration, but you'll need Jackson's jar package.Spring MVC3 annotations @responsebody automatically retu

SVM: Using SVM algorithm to realize handwritten image recognition (data set 50000 pictures)-jason Niu

ImportMnist_loader#Third-party Libraries fromSklearnImportSVMdefsvm_baseline (): Training_data, Validation_data, Test_data=Mnist_loader.load_data ()#TrainCLF =SVM. SVC () Clf.fit (training_data[0], training_data[1]) Predictions= [Int (a) forAinchclf.predict (test_data[0]) Num_correct= SUM (int (a = = y) forA, YinchZip (predictions, test_data[1])) Print("Baseline classifier using an SVM.") Print("%s of%s values correct."% (Num_correct, Len (test_data[1])))if __name__=="__main__": Svm_baseli

Python crawler technology (Get pictures from web page) +hierarchicalclustering hierarchical clustering algorithm to automatically get pictures from Web pages and automatically classify them according to the color of the image-jason Niu

Online tutorial too verbose, I hate a lot of useless nonsense, directly on, is dry!Web crawler? Non-supervised learning?Only two steps, only two?Is you kidding me?Is you OK?Come on, follow me, come on!.The first step: first, we get pictures from the Internet automatically downloaded to their own computer files, such as from the URL, download to the F:\File_Python\Crawler folder, the specific code please see http://www.cnblogs.com/yunyaniu/p/8244490.htmlThe second step: we use unsupervised learni

Jason and Java Object conversion examples

", " Num ": 2," Sex ":" Man1 "},{" Age ": 3," list ": []," name ":" Zhang2 "," num ": 3," Sex ":" Man2 "},{" Age ": 4," list ": []," name ":" Zhang3 "," num ": 4," Sex ":" Man3 "},{" Age ": 5," list ": []," name ":" Zhang4 "," num ": 5," Sex ":" Man4 "},{" Age ": 6," list ": []," Name ":" Zhang5 "," num ": 6," Sex ":" Man5 "},{" Age ": 7," list ": []," name ":" Zhang6 "," num ": 7," Sex ":" Man6 "},{" age ": 8," list ": [], "name": "Zhang7", "num": 8, "Sex": "Man7"},{"Age": 9, "list": [], "name"

20170313 ABAP Returns the value to HTTP (interface content return) in Jason format

Question 1:Back to Jason format information you can't get through this step,How can this be handled,Received the SCP System development reply, they need to adjust the method;(1) Call function to do return,It_zsmlscpnotice-functionname ='zmlscp1_fr0005'. It_zsmlscpnotice-bcpcode =Bcpcode. It_zsmlscpnotice-status =O_statu. It_zsmlscpnotice-msg =o_msg. It_zsmlscpnotice-result ="'. APPEND It_zsmlscpnotice. Clear:it_zsmlscpnotice. Call FUNCTION'zmlsc

Python3 Jason & Pickle

#Author by Andy#_ *_ Coding:utf-8 _*_Import JSONImport Pickledef sayhello (name): Print (' Hello%s '%name) Return ' Hello%s '%nameinfo={ ' Name ': ' Andy ', ' Age ': 20, ' Job ': ' Doctor ',}info1={ ' Name ': ' Andy ', ' Age ': 20, ' Job ': ' Doctor ', ' Func ': SayHello}# print (type (info))F=open (' E:\my python Study\\files\json Pickle.txt ', ' RB ')# Json.dumps (Info) #将字典转为字符串 (serialized)# json.dump (info,f) #=f.write (Json.dumps (info))# json.load (f)) #=json.l

JAVASCRIPR Learning (3) loops and Jason

JAVASCRIPR Learning (3) loops and Jason

Parsing Jason Data

/*** * {* "id": 2,* "title": "JSON title",* "Config": {* "width": 34,* "Height": 35* },* "Data": [* "JAVA",* "JavaScript",* "PHP"* ]* }* ** @param args*/public static void Main (string[] args){System.out.println ("----------------------------");String jsonstr = "{\" id\ ": 2," + "\" title\ ": \" JSON title\ "," + "\" config\ ": {" + "\" width\ ": 34,"+ "\" height\ ":", "+"}, \ "Data\": ["+" \ "Java\", \ "javascript\", \ "php\" "+"]} ";System.out.println (JSONSTR);System.out.println ("-----------

Angularjs get backstage Jason data displayed on the page

", "Andy", 20)); Ls.add (NewMember ("201", "Bill", 40)); Ls.add (NewMember ("501", "Cindy", 60)); Ls.add (NewMember ("901", "Eintein", 88)); Jsonarray Jarray=jsonarray.fromobject (LS); String JSON=jarray.tostring (); System.out.println ("Json=" +JSON); Out.print (JSON); Out.flush (); return; } Public voiddoget (httpservletrequest request, httpservletresponse response)throwsservletexception, java.io.IOException {doPost (request, response); }}Member Class Code: Packag

NN: Neural network algorithm advanced optimization method to further improve the accuracy rate of handwritten numeral recognition-jason NIU

was changed from quadratic cost to cross-enrtopy costs.class Crossentropycost (object): def fn (A, y): return np.sum (Np.nan_to_num (-y*np.log (a)-(1-y) *np.log (1-a) )def Delta (z, A, y ): return (a-y)Change of three:Change S function to Softmax functionclassSoftmaxlayer (object):def __init__(Self, n_in, n_out, p_dropout=0.0): self.n_in=n_in self.n_out=n_out self.p_dropout=p_dropout SELF.W=theano.shared (Np.zeros (n_in, n_out), Dtype=Theano.config.floatX), name='W', bo

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